Administering devices in dependence upon user metric vectors including relational metrics and location based device control

ABSTRACT

Exemplary embodiments of the present invention include a method for administering devices. Such exemplary methods include receiving a plurality of user metrics, creating a relational metric in dependence upon the plurality of user metrics, creating a user metric vector comprising at least one user metric and at least one relational metric, creating a user metric space comprising a plurality of metric ranges, and determining whether the user metric vector is outside the user metric space. If the user metric vector is outside a user metric space, exemplary embodiments include identifying an action, and executing the action.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The field of the invention is data processing, or, more specifically,methods, systems, and products for administering devices.

2. Description of Related Art

Conventional networks contain various devices. A user often uses thevarious devices, or adjusts the particular settings of the devices independence upon the user's current condition. That is, a user's currentcondition often motivates the user to change the settings of devices sothat the devices operate in a manner that more positively benefits theuser's current condition. For example, a user with a headache may bedisturbed by a powerful light. The user may dim the light, or turn thelight off, so that the light no longer disturbs the user. Conventionalnetworked devices, however, require user intervention to individuallyadminister the specific device in response to user condition. It wouldbe advantageous if there were a method of administering devices independence upon user condition that did not require user intervention.

SUMMARY OF THE INVENTION

Exemplary embodiments of the present invention include a method foradministering devices. Such exemplary methods include receiving aplurality of user metrics, creating a relational metric in dependenceupon the plurality of user metrics, creating a user metric vectorcomprising at least one user metric and at least one relational metric,creating a user metric space comprising a plurality of metric ranges,and determining whether the user metric vector is outside the usermetric space. if the user metric vector is outside a user metric space,exemplary embodiments include identifying an action, and executing theaction.

In many exemplary embodiments, creating a relational metric independence upon the plurality of user metrics includes filtering theuser metrics. In some exemplary embodiments, creating a relationalmetric in dependence upon the plurality of user metrics includesdetermining a relationship between a first filtered user metric and asecond filtered user metric. In some embodiments, determining arelationship between a first filtered user metric and a second filtereduser metric includes comparing a first filtered user metric with asecond filtered user metric. In many exemplary embodiments, creating arelational metric in dependence upon the plurality of user metricsincludes determining a magnitude of the relationship between the firstfiltered user metric and the second filtered user metric.

In some exemplary embodiments, creating relational metric in dependenceupon the plurality of user metrics includes determining whether theplurality of user metrics match a predefined metric pattern. Many ofsuch embodiments include retrieving a relational metric, if theplurality of user metrics match the predefined metric pattern. In someexemplary embodiments, creating a user metric vector includes at leastone user metric and at least one relational metric includes associatingat least one user metric with the user metric vector and associating atleast one relational metric with the user metric vector.

In some exemplary embodiments, identifying an action includesdetermining a user's location, and selecting an action ID in dependenceupon the user's location. In many such embodiments, identifying anaction also includes determining user movement; and selecting an actionID in dependence upon the user movement.

The foregoing and other objects, features and advantages of theinvention will be apparent from the following more particulardescriptions of exemplary embodiments of the invention as illustrated inthe accompanying drawings wherein like reference numbers generallyrepresent like parts of exemplary embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an exemplary architecture usefulin implementing methods for administering devices in accordance with thepresent invention.

FIG. 2 is a block diagram illustrating an exemplary services gateway.

FIG. 3 is a block diagram illustrating exemplary classes useful inimplementing methods for administering devices in accordance with thepresent invention.

FIG. 4 is a class relationship diagram illustrating an exemplaryrelationship among some of the exemplary classes of FIG. 3.

FIG. 5 is another class relationship diagram illustrating an exemplaryrelationship among some of the exemplary classes of FIG. 3.

FIG. 6 is a data flow diagram illustrating an exemplary method ofadministering devices in accordance with the present invention.

FIG. 7 is a data flow diagram illustrating an exemplary method ofexecuting an action.

FIG. 8 is a data flow diagram illustrating an exemplary method ofdetermining whether a user metric is outside a predefined metric rangefor the user in accordance with the present invention.

FIG. 9 is a data flow diagram illustrating an exemplary method ofadministering devices in accordance with the present invention.

FIG. 10 is a data flow diagram illustrating an exemplary method ofcreating a relational metric in accordance with the present invention.

FIG. 11 is a data flow diagram illustrating an exemplary method ofcreating a relational metric in accordance with the present invention.

FIG. 12 is a data flow diagram illustrating an exemplary method ofcreating a user metric vector and an exemplary method of creating ametric space in accordance with the present invention.

FIG. 13 is a data flow diagram illustrating an exemplary method ofdetermining whether a user metric vector is outside a user metric spacein accordance with the present invention

FIG. 14 is a data flow diagram illustrating an exemplary method ofcreating a dynamic action list in accordance with the present invention.

FIG. 15 is a data flow diagram illustrating an exemplary method ofidentifying an action in accordance with the present invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS Introduction

The present invention is described to a large extent in thisspecification in terms of methods for administering devices. Personsskilled in the art, however, will recognize that any computer systemthat includes suitable programming means for operating in accordancewith the disclosed methods also falls well within the scope of thepresent invention.

Suitable programming means include any means for directing a computersystem to execute the steps of the method of the invention, includingfor example, systems comprised of processing units and arithmetic-logiccircuits coupled to computer memory, which systems have the capabilityof storing in computer memory, which computer memory includes electroniccircuits configured to store data and program instructions, programmedsteps of the method of the invention for execution by a processing unit.The invention also may be embodied in a computer program product, suchas a diskette or other recording medium, for use with any suitable dataprocessing system.

Embodiments of a computer program product may be implemented by use ofany recording medium for machine-readable information, includingmagnetic media, optical media, or other suitable media. Persons skilledin the art will immediately recognize that any computer system havingsuitable programming means will be capable of executing the steps of themethod of the invention as embodied in a program product. Personsskilled in the art will recognize immediately that, although most of theexemplary embodiments described in this specification are oriented tosoftware installed and executing on computer hardware, nevertheless,alternative embodiments implemented as firmware or as hardware are wellwithin the scope of the present invention.

Definitions

“802.11” refers to a family of specifications developed by the IEEE forwireless LAN technology. 802.11 specifies an over-the-air interfacebetween a wireless client and a base station or between two wirelessclients.

“API” is an abbreviation for “application programming interface.” An APIis a set of routines, protocols, and tools for building softwareapplications.

“Bluetooth” refers to an industrial specification for a short-rangeradio technology for RF couplings among client devices and betweenclient devices and resources on a LAN or other network. Anadministrative body called the Bluetooth Special Interest Group testsand qualifies devices as Bluetooth compliant. The Bluetoothspecification consists of a ‘Foundation Core,’ which provides designspecifications, and a ‘Foundation Profile,’ which providesinteroperability guidelines.

“Coupled for data communications” means any form of data communications,wireless, 802.11b, Bluetooth, infrared, radio, internet protocols, HTTPprotocols, email protocols, networked, direct connections, dedicatedphone lines, dial-ups, serial connections with RS-232 (EIA232) orUniversal Serial Buses, hard-wired parallel port connections, networkconnections according to the Power Line Protocol, and other forms ofconnection for data communications as will occur to those of skill inthe art. Couplings for data communications include networked couplingsfor data communications. Examples of networks useful with variousembodiments of the invention include cable networks, intranets,extranets, internets, local area networks, wide area networks, and othernetwork arrangements as will occur to those of skill in the art. The useof any networked coupling among television channels, cable channels,video providers, telecommunications sources, and the like, is wellwithin the scope of the present invention.

“Driver” means a program that controls a device. A device (printer, diskdrive, keyboard) typically has a driver. A driver acts as translatorbetween the device and software programs that use the device. Eachdevice has a set of specialized commands that its driver knows. Softwareprograms generally access devices by using generic commands. The driver,therefore, accepts generic commands from a program and then translatesthem into specialized commands for the device.

“ESN” is an abbreviation for “Electronic Serial Number.” An ESN is aserial number programmed into a device, such as, for example, acoffeepot, to uniquely identify the device.

“Field”—In this specification, the terms “field” and “data element,”unless the context indicates otherwise, generally are used as synonyms,referring to individual elements of digital data. Aggregates of dataelements are referred to as “records” or “data structures.” Aggregatesof records are referred to as “tables” or “files.” Aggregates of filesor tables are referred to as “databases.” Complex data structures thatinclude member methods, functions, or software routines as well as dataelements are referred to as “classes.” Instances of classes are referredto as “objects” or “class objects.”

“HAVi” stands for ‘Home Audio Video interoperability,’ the name of avendor-neutral audio-video standard particularly for home entertainmentenvironments. HAVi allows different home entertainment and communicationdevices (such as VCRs, televisions, stereos, security systems, and videomonitors) to be networked together and controlled from one primarydevice, such as a services gateway, PC, or television. Using IEEE 1394,the ‘Firewire’ specification, as the interconnection medium, HAVi allowsproducts from different vendors to comply with one another based ondefined connection and communication protocols and APIs. Servicesprovided by HAVi's distributed application system include an addressingscheme and message transfer, lookup for discovering resources, postingand receiving local or remote events, and streaming and controllingisochronous data streams.

“HomePlug” stands for The HomePlug Powerline Alliance. HomePlug is anot-for-profit corporation formed to provide a forum for the creation ofopen specifications for high speed home powerline networking productsand services. The HomePlug specification is designed for delivery ofInternet communications and multimedia to homes through the home poweroutlet using powerline networking standards.

The HomePlug protocol allows HomePlug-enabled devices to communicateacross powerlines using Radio Frequency signals (RF). The HomPlugprotocol uses Orthogonal Frequency Division Multiplexing (OFDM) to splitthe RF signal into multiple smaller sub-signals that are thentransmitted from one HomPlug enabled-device to another HomePlug-enableddevice at different frequencies across the powerline.

“HTTP” stands for ‘HyperText Transport Protocol,’ the standard datacommunications protocol of the World Wide Web.

“ID” abbreviates “identification” as used by convention in thisspecification with nouns represented in data elements, so that ‘user ID’refers to a user identification and ‘userID’ is the name of a dataelement in which is stored a user identification. For a further exampleof the use of ‘ID’: ‘metric ID’ refers to a metric identification and‘metricID’ is the name of a data element in which is stored a metricidentification.

“IEEE 1394” is an external bus standard that supports data transferrates of up to 400 Mbps (400 million bits per second). Apple, whichoriginally developed EEE 1394, uses the trademarked name “FireWire.”Other companies use other names, such as i.link and Lynx, to describetheir 1394 products.

A single 1394 port can be used to connect up to 63 external devices. Inaddition to high speed, 1394 also supports isochronous datatransfer—delivering data at a guaranteed rate. This makes it ideal fordevices that need to transfer high levels of data in real-time, such asvideo.

“The Internet” is a global network connecting millions of computersutilizing the ‘internet protocol’ or ‘IP’ as the network layer of theirnetworking protocol stacks. The Internet is decentralized by design.Each computer on the Internet is independent. Operators for eachcomputer on the Internet can choose which Internet services to use andwhich local services to make available to the global Internet community.There are a variety of ways to access the Internet. Many onlineservices, such as America Online, offer access to some Internetservices. It is also possible to gain access through a commercialInternet Service Provider (ISP). An “internet” (uncapitalized) is anynetwork using IP as the network layer in its network protocol stack.

“JAR” is an abbreviation for ‘Java archive.’ JAR is a file format usedto bundle components used by a Java application. JAR files simplifydownloading applets, because many components (.class files, images,sounds, etc.) can be packaged into a single file. JAR also supports datacompression, which further decreases download times. By convention, JARfiles end with a ‘.jar’ extension.

“JES” stands for Java Embedded Server. JES is a commercialimplementation of OSGi that provides a framework for development,deployment, and installation of applications and services to embeddeddevices.

“LAN” is an abbreviation for “local area network.” A LAN is a computernetwork that spans a relatively small area. Many LANs are confined to asingle building or group of buildings. However, one LAN can be connectedto other LANs over any distance via telephone lines and radio waves. Asystem of LANs connected in this way is called a wide-area network(WAN). The Internet is an example of a WAN.

“LonWorks” is a networking platform available from Echelon®. Lon Worksis currently used in various network applications such as appliancecontrol and lighting control. The LonWorks networking platform uses aprotocol called “LonTalk” that is embedded within a “Neuron Chip”installed within Lon Works-enabled devices.

The Neuron Chip is a system-on-a-chip with multiple processors,read-write and read-only memory (RAM and ROM), and communication and I/Osubsystems. The read-only memory contains an operating system, theLonTalk protocol, and an I/O function library. The chip has non-volatilememory for configuration data and for application programs, which can bedownloaded over a LonWorks network to the device. The Neuron Chipprovides the first 6 layers of the standard OSI network model. That is,the Neuron Chip provides the physical layer, the data link layer, thenetwork layer, the transport layer, the session layer, and thepresentation layer.

The Neuron Chip does not provide the application layer programming.Applications for LonWorks networks are written in a programming languagecalled “Neuron C.” Applications written in Neuron C are typicallyevent-driven, and therefore, result in reduced traffic on the network.

“OSGI” refers to the Open Services Gateway Initiative, an industryorganization developing specifications for services gateways, includingspecifications for delivery of service bundles, software middlewareproviding compliant data communications and services through servicesgateways. The Open Services Gateway specification is a java basedapplication layer framework that gives service providers, networkoperator device makers, and appliance manufacturer's vendor neutralapplication and device layer APIs and functions.

The “OSI Model” or Open System Interconnection, model defines anetworking framework for implementing protocols in seven layers. Controlis passed from one layer to the next, starting at the application layerin one network station, proceeding to the bottom layer, over the channelto the next network station and back up the hierarchy.

The seventh layer of the OSI model is the application layer. Theapplication layer supports application and end-user processes. Theapplication layer provides application services for file transfers,email, and other network software services.

The sixth layer of the OSI model is the presentation layer. Thepresentation layer provides independence from differences in datarepresentation. The presentation layer translates from application dataformat to network data format, and vice versa. The presentation layer issometimes called the “syntax layer.”

The fifth layer of the OSI model is the session layer. The session layerestablishes, manages, and terminates connections between networkedapplications. The session layer sets up, coordinates, and terminatesconversations, exchanges, and dialogues between networked applications.

The fourth layer of the OSI model is the transport layer. The transportlayer provides transparent transfer of data between networked systems,or hosts. The transport layer is also responsible for flow control andensures complete data transfer.

The third layer of the OSI model is the network layer. The network layercreates logical paths, known as virtual circuits, for transmitting datafrom one network node to another network node. Routing, forwarding,addressing, and packet sequencing are functions of the network layer.

The second layer of the OSI model is the data link layer. The data linklayer decodes data packets into bits and codes bits into data packets.The data link layer provides a transmission protocol and manages dataflow transmission in the in the physical layer.

The data link layer is divided into two sublayers. The first sublayer ofthe data link layer is the Media Access Control (MAC) layer. The MACsublayer controls access and permission for a computer on a network totransmit data. The second sublayer of the data link layer is the LogicalLink Control (LLC) layer. The LLC layer controls data flow transmissionin the physical layer.

The first layer of the OSI model is the physical layer. The physicallayer transmits the bit stream (electrical impulse, light or radiosignal) through the physical network at the electrical and mechanicallevel. The physical layer provides the hardware for sending andreceiving data.

“SMF” stands for “Service Management Framework™” available from IBM®.SMF is a commercial implementation of OSGi for management of networkdelivered applications on services gateways.

“USB” is an abbreviation for “universal serial bus.” USB is an externalbus standard that supports data transfer rates of 12 Mbps. A single USBport can be used to connect up to 127 peripheral devices, such as mice,modems, and keyboards. USB also supports Plug-and-Play installation andhot plugging.

“WAP” refers to the Wireless Application Protocol, a protocol for usewith handheld wireless devices. Examples of wireless devices useful withWAP include mobile phones, pagers, two-way radios, and hand-heldcomputers. WAP supports many wireless networks, and WAP is supported bymany operating systems. Operating systems specifically engineered forhandheld devices include PalmOS, EPOC, Windows CE, FLEXOS, OS/9, andJavaOS. WAP devices that use displays and access the Internet run“microbrowsers.” The microbrowsers use small file sizes that canaccommodate the low memory constraints of handheld devices and thelow-bandwidth constraints of wireless networks.

The “X-10” means the X-10 protocol. Typical X-10 enabled devicescommunicate across AC powerline wiring, such as existing AC wiring in ahome, using an X-10 transmitter and an X-10 receiver. The X-10transmitter and the X-10 receiver use Radio Frequency (RF) signals toexchange digital information. The X-10 transmitter and the X-10 receivercommunicate with short RF bursts which represent digital information. ABinary 1 is represented by a 1 millisecond burst of 120 KHz. and aBinary 0 by the absence of 120 KHz burst followed by the presence of aburst.

In the X-10 protocol, data is sent in data strings called frames. Theframe begins with a 4 bit start code designated as “1110.” Following thestart code, the frame identifies a particular domain, such as house,with a 4 bit “house code,” and identifies a device within that domainwith a 4 bit “devices code.” The frame also includes a command string of8 bits identifying a particular preset command such as “on,” “off,”“dim,” “bright,” “status on,” “status off,” and “status request.”

Exemplary Architecture

FIG. 1 is a block diagram of exemplary architecture useful inimplementing methods of administering devices in accordance withembodiments of the present invention. The architecture of FIG. 1includes a domain (118). The term “domain” in this specification means aparticular networked environment. Examples of various domains includehome networks, car networks, office network, and others as will occur tothose of skill in the art.

The domain (118) of FIG. 1 includes a services gateway (106). A servicesgateway (106) is, in some exemplary architectures, an OSGi compatibleservices gateway (106). While exemplary embodiments of methods foradministering devices are described in this specification using OSGi,many other applications and frameworks, will work to implement themethods of administering devices according to the present invention, andare therefore also well within the scope of the present invention.Commercial implementations of OSGi, such as JES and SMF, are also usefulin implementing methods for administering devices.

In the exemplary architecture of FIG. 1, the services gateway (126)includes a services framework (126). The services framework (126) ofFIG. 1 is a hosting platform for running ‘services.’ Services are themain building blocks for creating applications in the OSGi. An OSGiservices framework (126) is written in Java and therefore, typicallyruns on a Java Virtual Machine (JVM) (150).

The exemplary architecture of FIG. 1 includes a DML (108). “DML” (108)is an abbreviation for Domain Mediation Layer. In many embodiments ofthe architecture of FIG. 1, the DML (108) is application software usefulin implementing methods of administering devices in accordance with thepresent invention. In some embodiments of the present invention, the DMLis OSGi compliant application software, and is therefore implemented asa service or a group of services packaged as a bundle installed on theservices framework (126). In this specification, DMLs are oftendiscussed in the context of OSGi. However, the discussion of OSGI is forexplanation and not for limitation. In fact, DMLs according to variousembodiments of the present invention can be implemented in anyprogramming language, C, C++, COBOL, FORTRAN, BASIC, and so on, as willoccur to those of skill in the art, and DMLs developed in languagesother than Java are installed directly upon an operating system oroperating environment rather than a JVM.

In the exemplary architecture of FIG. 1, the services gateway (106) iscoupled for data communications with a metric sensor (406). A metricsensor (406) is a device that reads an indication of a user's condition,and creates a user metric in response to the indication of the user'scondition. An “indication of a user's condition” is a quantifiableaspect of a user's condition and a quantity measuring the aspect. Forexample, a quantifiable aspect of a user's condition is a bodytemperature of 99.2 degrees Fahrenheit. Examples of quantifiable aspectsof a user's condition include body temperature, heart rate, bloodpressure, location, galvanic skin response, and others as will occur tothose of skill in the art.

A “user metric” is a data structure representing an indication of usercondition. In many examples of methods for administering devices inaccordance with the present invention, a user metric is implemented as adata structure, class, or object that includes a userID field, ametricID field, and a metric value field. A typical userID fieldidentifies the user whose indication of condition is represented by themetric. A typical metricID field identifies the quantifiable aspect ofuser condition the metric represents, such as, for example, bloodpressure, heart rate, location, or galvanic skin response. A typicalmetric value field stores a quantity measuring the aspect of a user'scondition.

Wearable and wireless heart rate monitors, galvanic skin responsemonitors, eye response monitors, and breathing monitors useful as oreasily adaptable for use as metric sensors are currently available fromQuibit Systems, Inc. The ‘Polar’ series of heart rate monitors from BodyTrends, Inc., and the magnetoelastic gastric pH sensors from SentecCorporation are other examples of readily available biomedical sensorsuseful as or easily adaptable for use as metric sensors.

In order for a conventional sensor, such as a biomedical sensor, to beuseful as a metric sensor that transmits multiple metric types in adomain containing multiple users, the sensor advantageously transmitsnot only a value of the each aspect it measures, but also transmits auser ID and a metricID. The user ID is useful because typicalembodiments of the present invention include a DML capable ofadministering devices on behalf of many users simultaneously. ThemetricID is useful because a single user may employ more than one metricsensor at the same time or employ a metric sensor capable of monitoringand transmitting data regarding more than one aspect of user condition.All wireless sensors at least transmit a metric value according to somewireless data communications protocol. To the extent that any particularsensor ‘off-the-shelf’ does not also transmit user ID or metricID, sucha sensor is easily adapted, merely by small modifications of itscontrolling software, also to include in its transmissions user IDs andmetricID.

Although it is expected that most DMLs will support metric IDs and userIDs, it is possible, under some circumstances within the scope of thepresent invention, to use an off-the-shelf sensor as a metric sensoreven if the sensor does not provide metric ID and user ID in its outputtelemetry. Consider an example in which only a single person inhabits adomain having device controlled or administered by a DML tracking only asingle metric, such as, for example, heart rate. A DML tracking only onemetric for only one user could function without requiring a metric typecode in telemetry received from the metric sensor because, of course,only one type of metric is received. In this example, strictly speaking,it would be possible for an off-the-shelf, Bluetooth-enabled heart ratesensor, such as a ‘Polar’ sensor from Body Trends, to function as ametric sensor. This example is presented only for explanation, becauseas a practical matter it is expected that most DMLs according toembodiments of the present invention will usefully and advantageouslyadminister more than one type of metric (therefore needing a metric IDcode in their telemetry) on behalf of more than one user (thereforeneeding a user ID in their telemetry).

In many embodiments of the present invention, the metric sensor isadvantageously wirelessly coupled for data communications with theservices gateway (106). In many alternative embodiments, the metricsensor transmits the user metric to the DML through a services gatewayusing various protocols such as Bluetooth, 802.11, HTTP, WAP, or anyother protocol that will occur to those of skill in the art.

In the exemplary architecture of FIG. 1, the domain (118) includes adevice (316) coupled for data communications with the services gateway(106) across a LAN (105). In many embodiments of the present invention,a domain (118) will include many devices. A home domain, for example,may include a home network having a television, numerous lights, arefrigerator, a freezer, a coffee pot, a dishwasher, a dryer, a CDplayer, a DVD player, a personal video recorder, or any othernetworkable device that will occur to those of skill in the art. Forease of explanation, the exemplary architecture of FIG. 1 illustratesonly three devices (316), but the use of any number of devices is wellwithin the scope of the present invention.

To administer the device (316), the DML must have the device class forthe device containing accessor methods that get and set attributes onthe device, and in some cases, a communication class that provides theprotocols needed to communicate with the device. In some examples of thearchitecture of FIG. 1, a DML has pre-installed upon it, device classesand communications classes for many devices that the DML supports.

To the extent the DML does not have a preinstalled device class andcommunications class for a particular device, the DML can obtain thedevice class and communications class in a number of ways. One way theDML obtains the device class and communications class for the device isby reading the device class and the communications class from thedevice. This requires the device have enough installed memory to storethe device class and communications class. The DML can also obtain thedevice class and communications class from devices that do not containthe device class or communications class installed upon them. One waythe DML obtains the device class and communications class is by readinga device ID from the device, searching the Internet for the device classand communications class, and downloading them. Another way the DMLobtains the device class and communications class is by reading anetwork location from the device downloading, from the network location,the device class and communications class. Three ways have beendescribed for obtaining the device classes and communications classesneeded to administer devices in accordance with the present invention.Other methods will also occur to those of skill in the art.

The exemplary architecture of FIG. 1 includes a non-domain entity (102)that is coupled for data communications with the services gateway (106)across a WAN (104). A “non-domain entity” is any computing device ornetwork location coupled for data communications to the domain but notwithin the domain. The phrase “non-domain entity” is broad and itsinclusion in the architecture of FIG. 1 acknowledges that in manyembodiments of architecture useful in implementing methods ofadministering devices in accordance with the present invention, a givendomain is coupled for data communications with outside non-domainentities.

An example of a non-domain entity is a web server (outside the domain)of a manufacturer of the device (316) installed within the domain. Themanufacturer may operate a website that makes available for downloaddrivers for the device, updates for the device, or any other informationor software for the device. Drivers, updates, information or softwarefor the device are downloadable to the device across a WAN and throughthe services gateway.

FIG. 2 is a block diagram of an exemplary services gateway (106) usefulin implementing methods of administering devices according to thepresent invention. The services gateway (106) of FIG. 2 is, in someexemplary architectures useful in embodiments of the present invention,an OSGi compatible services gateway (106). While exemplary embodimentsof methods for administering a device are described in thisspecification using OSGi, many other applications and frameworks otherthan OSGi will work to implement methods of administering devicesaccording to the present invention and are therefore well within thescope of the present invention. Commercial implementations of OSGi, suchas JES and SMF, are also useful in implementing methods of the presentinvention.

OSGi Stands for ‘Open Services Gateway Initiative.’ The OSGispecification is a Java-based application layer framework that providesvendor neutral application and device layer APIs and functions forvarious devices using arbitrary communication protocols operating innetworks in homes, cars, and other environments. OSGi works with avariety of networking technologies like Ethernet, Bluetooth, the ‘Home,Audio and Video Interoperability standard’ (HAVi), IEEE 1394, UniversalSerial Bus (USB), WAP, X-10, Lon Works, HomePlug and various othernetworking technologies. The OSGi specification is available for freedownload from the OSGi website at www.osgi.org.

The services gateway (130) of FIG. 2 includes a service framework (126).In many example embodiments the service framework is an OSGi serviceframework (126). An OSGi service framework (126) is written in Java andtherefore, typically runs on a Java Virtual Machine (JVM). In OSGi, theservice framework (126) of FIG. 1 is a hosting platform for running‘services’ (124). The term ‘service’ or ‘services’ in this disclosure,depending on context, generally refers to OSGi-compliant services.

Services (124) are the main building blocks for creating applicationsaccording to the OSGi. A service (124) is a group of Java classes andinterfaces that implement a certain feature. The OSGi specificationprovides a number of standard services. For example, OSGi provides astandard HTTP service that creates a web server that can respond torequests from HTTP clients.

OSGi also provides a set of standard services called the Device AccessSpecification. The Device Access Specification (“DAS”) provides servicesto identify a device connected to the services gateway, search for adriver for that device, and install the driver for the device.

Services (124) in OSGi are packaged in ‘bundles’ (121) with other files,images, and resources that the services (124) need for execution. Abundle (121) is a Java archive or ‘JAR’ file including one or moreservice implementations (124), an activator class (127), and a manifestfile (125). An activator class (127) is a Java class that the serviceframework (126) uses to start and stop a bundle. A manifest file (125)is a standard text file that describes the contents of the bundle (121).

In the exemplary architecture of FIG. 2 includes a DML (108). In manyembodiments of the present invention, the DML is an OSGi service thatcarries out methods of administering devices. The DML (108) of FIG. 2 ispackaged within a bundle (121) and installed on the services framework(126).

The services framework (126) in OSGi also includes a service registry(128). The service registry (128) includes a service registration (129)including the service's name and an instance of a class that implementsthe service for each bundle (121) installed on the framework (126) andregistered with the service registry (128). A bundle (121) may requestservices that are not included in the bundle (121), but are registeredon the framework service registry (128). To find a service, a bundle(121) performs a query on the framework's service registry (128).

Exemplary Classes and Class Cooperation

FIG. 3 is a block diagram illustrating exemplary classes useful inimplementing methods for administering devices in accordance with thepresent invention. The exemplary classes of FIG. 3 are presented as anaid to understanding of the present invention, not for limitation. Whilemethods of administering devices in accordance with the presentinvention are discussed generally in this specification in terms ofJava, Java is used only for explanation, not for limitation. In fact,methods of administering devices in accordance with the presentinvention can be implemented in many programming languages includingC++, Smalltalk, C, Pascal, Basic, COBOL, Fortran, and so on, as willoccur to those of skill in the art.

The class diagram of FIG. 3 includes an exemplary DML class (202). Aninstance of the exemplary DML class (202) of FIG. 3 provides membermethods that carry out the steps useful in administering devices inaccordance with the present invention. The exemplary DML class of FIG. 3is shown with an Activator.start( ) method so that the DML can bestarted as a service in an OSGi framework. Although only one membermethod is shown for this DML, DMLs in fact will often have more membermethods as needed for a particular embodiment. The DML class of FIG. 3also includes member data elements for storing references to servicesclasses, often created by the DML's constructor. In this example, theDML provides storage fields for references to a metric service (552), ametric range service (558), a communication service (554), an actionservice (560), a device service (556), a metric vector service (559) anda metric space service (561), and dynamic action list service (563).

The metric service class (204) of FIG. 3 provides member methods thatreceive user metrics from a DML and create, in response to receiving theuser metrics from the DML, an instance of a metric class. The metricservice class (204) of FIG. 3 includes a createMetric(UserID, MetricID,MetricValue) member method (562). The createMetric( ) member method is,in some embodiments, a factory method parameterized with a metric IDthat creates and returns a metric object in dependence upon the metricID. In response to getting a user metric from the DML, the exemplaryinstance of the metric service class (204) of FIG. 3 creates an instanceof a metric class and returns to the DML a reference to the new metricobject.

Strictly speaking, there is nothing in the limitations of the presentinvention that requires the DML to create metric object through afactory method. The DML can for example proceed as illustrated in thefollowing pseudocode segment: // receive on an input stream a metricmessage // extract from the metric message a userID, // a metric ID, anda metric value, so that: int userID = // userID from the metric messageint metricID = // metricID from the metric message int metricValue = //metric value from the metric message Metric aMetric = new Metric( );aMetric.setUserID (userID); aMetric.setMetricID(metricID);aMetric.setMetricValue(metricValue); aMetric.start ( );

This example creates a metric object and uses accessor methods to loadits member data. This approach provides exactly the same class of metricobject for each metric, however, and there are circumstances whenmetrics advantageously utilize different concrete class structures. Inthe case of metrics for heart rate and blood pressure, for example, bothmetric values may be encoded as integers, where a metric value for polarcoordinates on the surface of the earth from a GPS transceiver, forexample, may advantageously be encoded in a more complex data structure,even having its own Location class, for example. Using a factory methodeases the use of more than one metric class. A DML using a factorymethod to create metric objects can proceed as illustrated in thefollowing exemplary pseudocode segment: // receive on an input stream ametric message // extract from the metric message a userID, // a metricID, and a metric value, so that: int userID = // userID from the metricmessage int metricID = // metricID from the metric message intmetricValue = // metric value from the metric message Metric aMetric =MetricService.createMetricObject(userID, metricID,    metricValue);aMetric.start( );

This example relies on the factory method createMetric( ) to set theparameter values into the new metric object. A metric service and afactory method for metric object can be implemented as illustrated inthe following pseudocode segment: // // Metric Service Class // classMetricService {    public static Metric createMetricObject(userID,metricID, metricValue)    {     Metric aMetric;     switch(metricID)    {       case 1: aMetric = new HeartRateMetric(userID, metricID,metricValue);           break;       case 2: aMetric =           newBloodPressureMetric(userID, metricID, metricValue);           break;      case 3: aMetric = new GPSMetric(userID, metricID metricValue);          break;      } // end switch( )      return aMetric;    } //end createMetric( ) } // end class MetricService

MetricService in this example implements a so-called parameterizedfactory design pattern, including a factory method. In this example, thefactory method is a member method named ‘createMetricObject( ).’CreateMetricObject( ) accepts three parameters, a user ID, a metric ID,and a metric value. CreateMetricObject( ) implements a switch statementin dependence upon the metric ID to select and instantiate a particularconcrete metric class. The concrete metric classes in this example areHeartRateMetric, BloodPressureMetric, and GPSMetric, each of whichextends a Metric base class. CreateMetricObject( ) returns to thecalling DML a reference to a new metric object. The call from the DML:Metric aMetric=MetricService.createMetricObject(userID, metricID,metricValue);

is polymorphic, utilizing a reference to the base class Metric, so thatthe calling DML neither knows nor cares which class of metric object isactually instantiated and returned. The following is an example ofextending a Metric base class to define a concrete metric classrepresenting a user's location on the surface of the earth extending aMetric base class: Class GPSMetric extends Metric {     int myUserID;    int myMetricID     class GPSLocation {         Latitude myLatitude;        Longitude myLongitude;     }     Class Latitude {         Stringdirection;         int degrees;         int minutes;         intseconds;     }     Class Longitude {         String direction;        int degrees;         int minutes;         int seconds;     }    GPSLocation myLocation;     GPSMetric(int userID, int metricIDGPSLocation metricValue) {         myUserID = userID;         myMetricID= metricID:         myLocation = metricValue;     } }

The example concrete class GPSMetric provides storage for latitude andlongitude. GPSMetric provides a constructor GPSMetric( ) that takesinteger arguments to set userID and metricID but expects its metricValueargument to be a reference to a GPSLocation object, which in turnprovides member data storage for latitude and longitude.

The class diagram of FIG. 3 includes an exemplary metric class (206).The exemplary metric class (206) of FIG. 3 represents a user metric. Auser metric comprises data describing an indication of user condition.An indication of a user's condition is a quantifiable aspect of a user'scondition and a quantity measuring the aspect. Examples of quantifiableaspects of a user's condition include body temperature, heart rate,blood pressure, location, galvanic skin response, or any other aspect ofuser condition as will occur to those of skill in the art.

The exemplary metric class (206) of FIG. 3 includes a user ID field(486), a metric ID field (488), a value field (490). The user ID field(486) identifies the user. The metric ID (488) field identifies the usermetric that an instance of the metric class represents. That is, thekind of user metric. The value field (490) includes a value of the usermetric.

The exemplary metric class of FIG. 3 also includes data storage for ametric action list (622). A metric action list is a data structurecontaining action IDs identifying actions that when executed administerdevices in a manner that affect the same aspect of user conditionrepresented by the metric. A metric for body temperature, for example,may have an associated metric action list including an action ID thatwhen executed results in turning on a ceiling fan. In many examples ofmethods for administering devices, the action IDs in the metric actionlists are used to identify action IDs for inclusion in a dynamic actionlist.

This exemplary metric class (206) is an example of a class that can invarious embodiments be used in various embodiments as a generic class,instances of which can be used to store or represent more than one typeof metric having identical or similar member data elements as discussedabove. Alternatively in other embodiments, a class such as this examplemetric class (206) can be used as a base class to be extended byconcrete derived classes each of which can have widely disparate memberdata type, also described above.

The class diagram of FIG. 3 includes an exemplary relational metricservice class (684). The exemplary relational metric service classincludes a member method, createRelationalMetric( ) (686). In manyembodiments, createRelationlMetric( ) (686) determines a relationshipamong the user metrics in metric cache and instantiates an relationalmetric representing the determined relationship among the user metricsin metric cache. In other embodiments, createRelatinoalMetric( )compares the user metrics in metric cache with a set of predefinedmetrics that together make-up a predefined metric pattern. If the usermetrics in metric cache match the predefined metrics making up thepredefined metric pattern, createRelationlMetric retrieves a pre-createdrelational metric representing the relationship defined by thepredefined metric pattern.

The class relationship diagram of FIG. 3 includes a relational metric.The relational metric is a metric created in dependence upon the usermetrics in metric cache or created in anticipation of user metricsarriving in cache. That is, a relational metric is, in some cases,created as a result of determining a relationship among the user metricsin metric cache. In other cases, a relational metric is a metric createdin dependence of predetermined patterns of predetermined metrics. Suchpredetermined relational metrics are often then selected, from arelational database, in dependence upon the user metrics in metriccache.

The exemplary relational metric of FIG. 3 includes a userID fieldidentifying the user. The relational metric of FIG. 3 includes a metricID. The relational metric also includes a value field (490). In manycases, the value field typically represents the magnitude of theparticular relationship represented by the relational metric. In someexamples, a relationship record can have more than one value fieldrepresenting different aspect of the relational metric. For example, arelational metric for ‘moving,’ can have a value field that indicatesdirection, and another value field that indicates speed.

The class diagram of FIG. 3 includes a metric vector service (207). Themetric vector service class (207) of FIG. 3 provides member methods thatcreate, in response to receiving the user metrics from the metricservice and relational metrics from a relational metric service, aninstance of a metric vector class. In many example embodiments, thecreateMetric vectorObject( ) member method (565) identifies from ametric vector list a metric vector ID for the user metric vector independence upon the user ID, and the metric ID of the user metrics andrelational metrics. If there is not a metric vector in the metric vectorservice's metric vector list, the metric vector service instantiates oneand stores its metric vector ID in a metric vector table, indexed by theassociated user ID and metric ID. Creating a metric vector object can beimplemented as illustrated in the following pseudocode segment: //receive a metric on input stream // extract its userID as an integer //instantiate a metric object Metric newMetric =metricService.createMetricObject(metricID); int MetricVectorID = 0;if((MetricVectorID = MetricVectorList.get(userID, metricID)) == null) {    MetricVector newMetricVector =    MetricVectorService.createMetricVectorObject(userID,     metricID);    MetricVectorID = newMetricVector.MetricVectorID;    MetricVectorList.add(MetricVectorID, newMetricVector)     }

In the pseudocode example above, if the metric vector service receives ametric or relational metric having a userID for which it has no metricvector identified in the metric vector service's metric vector table,the metric vector service creates a new metric vector having a newmetric vector ID for the user and adds the metric vector to the metricvector list.

The class diagram of FIG. 3 includes a metric vector class (606).Objects of the metric vector class represent a complex indication ofuser condition. A user metric vector typically includes a collection ofa user metrics each representing a single quantifiable aspect of auser's condition and a quantity measuring the aspect and a relationalmetric created from, or in anticipation of, user metrics in metriccache. A user metric vector comprised of a plurality of disparate usermetrics therefore represents a complex indication of user conditionhaving multiple quantifiable aspects of a user's condition and multiplequantities measuring the aspects. The metric vector class (606) includesdata elements for storing a user ID (486) identifying the user and ametric list (652) for storing references to a plurality of disparatemetric objects.

The exemplary metric vector (606) of FIG. 3 also includes data storagefor a dynamic action list (626). A dynamic action list is a list ofaction IDs created in dependence upon metric action lists that areassociated with the particular metrics of the user metric vector thatare outside their corresponding metric ranges of the user metric space.That is, each metric of the metric vector that is outside itscorresponding metric range has an associated metric action list. Adynamic action list includes action IDs identified in dependence uponthose metric action lists associated with the particular metrics of auser metric vector outside their corresponding metric ranges of the usermetric space. A dynamic action list advantageously provides a list ofaction IDs tailored to the user's current condition.

Objects of the exemplary metric vector class also typically includemember methods for determining if the metric vector is outside a usermetric space. This exemplary metric vector class is an example of aclass that can in various embodiments be used as a generic class,instances of which can be used to store or represent more than one typeof vector having identical or similar member data elements.Alternatively in other embodiments, a class such as this example metricvector class can be used as a base class to be extended by concretederived classes each of which can have disparate member data types.

The class diagram of FIG. 3 includes metric range service class (208).The metric range service class (208) provides member methods thatinstantiate an instance of a metric range class. The metric rangeservice class (208) of FIG. 3 includes a createRangeObject(UserID,MetricID) member method (572). The createRangeObject( ) member method isa factory method parameterized with a userID and a metric ID thatcreates a metric range object in dependence upon the userID and metricID. The createRangeObject( ) factory method returns a reference to themetric range object to the metric vector. The createRangeObject( ) is aparameterized factory method that can be implemented using the samedesign patterns outlined by the exemplary psuedocode provided in thedescription of the createMetricObject( ) factory method.

The class diagram of FIG. 3 includes an exemplary metric range class(210). An instance of the exemplary metric range class represents apredefined metric range for a user for a metric or for a relationalmetric. A maximum value and minimum value in a metric range object arecompared with a metric value to determine whether the metric value ofthe metric object is outside a predefined metric range. The exemplarymetric range class (210) of FIG. 3 includes range ID field (463)identifying the metric range, and a metric ID field (462) identifyingthe user metric. The exemplary metric range class (210) of FIG. 3includes a user ID field (464) identifying the user. The metric rangeclass also includes a Max field (468) and a Min field (470) containing amaximum value and a minimum value defining a metric range.

The exemplary metric range class (210) of FIG. 3 is an example of aso-called data object, that is, a class that serves only as a containerfor data, with little or no processing done on that data by the membermethods of the class. In this example, objects of the metric range classare used primarily to transfer among other objects the minimum andmaximum values of a metric range. The metric range class of FIG. 3includes a default constructor (not shown), but strictly speaking, wouldneed no other member methods. If the metric range class were providedwith no other member methods, cooperating object could access its memberdata elements directly by coding, such as, for example:“someMetricRange.max” or “someMetricRange.min.” The particular examplein this case (210), however, is illustrated as containing accessormethods (471, 473) for the minimum and maximum values of its range, apractice not required by the invention, but consistent with programmingin the object oriented paradigm.

The class diagram of FIG. 3 includes a metric space service class (209).The metric space service class (209) includes a member methodcreateMetricSpace( ) that searches a metric space list, or other datastructure, to identify a metric space for a user. If no such metricspace exists, createMetricSpace( ) instantiates one and stores themetric space ID in the metric space list. Creating a metric space objectcan be implemented by way of the following exemplary psuedocode: //extract its userID and MetricVector ID as an integer // instantiate ametric space object MetricVector newMetricVector    =MetricVectorService.createMetricVectorObject(userID,    MetricVectorID); if((spaceID = MetricSpaceList.get(userID,metricvectorID)) == null) { MetricSpace newMetricSpace =    MetricSpaceService.createMetricSpace(userID,     MetricVectorID);MetricSpaceID = newMetricSpace.SpaceID; MetricSpaceList.add(SpaceID,newMetricSpace) }

In the pseudo code example above, the metric space service searches ametric space list for a metric space. If the list contains no metricspace for the userID and metric vector ID, thenMetricSpaceService.createMetricSpace(userID, MetricVectorID) creates anew metric space with a new metric space ID.

The class diagram of FIG. 3 includes a metric space class. The usermetric space is comprised of a plurality of user metric ranges fordisparate user metrics and relational metrics. The exemplary metricspace includes data elements for storing a user ID (405) identifying theuser and a space ID (908) identifying the metric space. The metric space(610) of FIG. 3 also includes data storage (655) for a list ofreferences to disparate metric ranges for user metrics and relationalmetrics. The disparate metric ranges of the metric space correspond inkind to the metrics in the user metric vector. That is, in typicalembodiments, the user metric vector includes a set of disparate currentuser metrics and relational metrics and the user metric space includes aset of corresponding metric ranges for the user.

The class diagram of FIG. 3 includes an action service class (217). Theaction service class includes member methods that instantiate a metricaction list for a user metric or a relational metric, instantiate actionobjects, store references to the action objects in the action list, andreturn to a calling metric a reference to the action list, all of whichcan be implemented as illustrated by the following exemplary pseudocodeActionService class: // // Action Service Class // class ActionService {   public static Action createActionList(userID, MetricID)    {    ActionList anActionList = new ActionList( );     int actionID;    // with finds of database action records storing data describingactions     for(/* each action record matching userID and metricID */) {      // obtain action ID from each matching action record      actionID = // action ID from matching database record       // *the action constructors below obtain from a device       // service alist of devices administered by the action object       switch(actionID)       {          case 1: Action anAction1 = new Action1(DeviceService,actionID);              anActionList.add(anAction1);              break;         case 2: Action anAction2 = new Action2(DeviceService,actionID);              anActionList.add(anAction2);              break;         case 3: Action anAction3 = new Action3(DeviceService,actionID);              anActionList.add(anAction3);              break;         case 4: Action anAction4 = new Action4(DeviceService,actionID);              anActionList.add(anAction4);              break;         case 5: Action anAction5 = new Action5(DeviceService,actionID);              anActionList.add(anAction5);              break;       } // end switch( )      } // end for( )      return anActionList;   } // end createActionListObject( ) } // end class ActionService

The createActionList( ) method in ActionService class instantiates ametric action list for a user metric with “ActionList anActionList=newActionList( ).” CreateActionList( ) then searches an action record tablein a database for records having user IDs and metric IDs matching itscall parameters. For each matching record in the table,createActionList( ) instantiates an action object through its switchstatement. The switch statement selects a particular concrete derivedaction class for each action ID retrieved from the action record table.CreateActionList( ) stores a references to each action object in theaction list with “anActionList.add( ).” CreateActionList( ) returns areference to the action list with “return anActionList.”

The class diagram of FIG. 3 includes an exemplary action class (216). Aninstance of the action class represents an action that when executedresults in the administration of a device. The exemplary action class ofFIG. 3 includes an action ID field (450). The doAction( ) method (456)in the exemplary action class (216) is programmed to obtain a devicelist (458) from, for example, a call to DeviceService.createDeviceList(). Action.doAction( ) (456) typically then also is programmed to callinterface methods in each device in its device list to carryout thedevice controlling action.

The class diagram of FIG. 3 includes a dynamic action list service. Thedynamic action list service of FIG. 3 includes a member methodcreateDynamicList( ) (569). In many embodiments, createDynamicList iscalled by member methods within a user metric vector and parameterizedwith action IDs retrieved from metric action lists associated with theparticular metrics that are outside their corresponding metric ranges.CreateDynamicList creates a dynamic action list including action IDsidentified in dependence upon the metric IDs retrieved from the metricaction lists and returns to its caller a reference to the dynamic actionlist.

The class diagram of FIG. 3 includes a device service class (218). Thedevice service class provides a factory method namedcreateDeviceList(actionID) that creates a list of devices and returns areference to the list. In this example, createDeviceList( ) operates ina fashion similar to ActionService.createActionList( ) described above,by instanting a device list, searching through a device table for deviceIDs from device records having matching action ID entries, instantiatinga device object of a concrete derived device class for each, adding tothe device list a reference to each new device object, and returning toa calling action object a reference to the device list. In this example,however, the factory method createDeviceList( ) not only retrieves adevice ID from its supporting data table, but also retrieves a networkaddress or communications location for the physical device to becontrolled by each device object instantiated, as illustrated by thefollowing exemplary pseudocode: // // Device Service Class // classDeviceService {    public static Device createDeviceList(actionID)    {    DeviceList aDeviceList = new DeviceList( );     int deviceID;     //with finds of database device records storing data describing devices    for(/* each device record matching actionID */) {       // obtaindevice ID and device address from each matching device record      deviceID = // device ID from matching database record      deviceAddress = // device ID from matching database record      // reminder: the device constructors below obtain from a device      // service a list of devices administered by the device object      switch(deviceID)       {        case 1: Device aDevice = newDevice1(CommsService,              deviceAddress, deviceID);             break;        case 2: Device aDevice = newDevice2(CommsService              deviceAddress, deviceID);             break;        case 3: Device aDevice = newDevice3(CommsService              deviceAddress, deviceID);             break;        case 4: Device aDevice = newDevice4(CommsService              deviceAddress, deviceID);             break;        case 5: Device aDevice = newDevice5(CommsService              deviceAddress, deviceID);             break;       } // end switch( )      aDeviceList.add(aDevice);     } // end for( )     returnaDeviceList;   } // end createDeviceListObject( ) } // end classDeviceService

The createDeviceList( ) method in DeviceService class instantiates adevice list for a metric with “DeviceList aDeviceList=new DeviceList().” CreateDeviceList( ) then searches a device record table in adatabase for records having action IDs matching its call parameter. Foreach matching record in the table, createDeviceList( ) instantiates adevice object through its switch statement, passing three parameters,CommsService, deviceAddress, and deviceID. CommsService is a referenceto a communications service from which a device object can obtain areference to a communications object for use in communicating with thephysical device controlled by a device object. DeviceAddress is thenetwork address, obtained from the device table as described above, ofthe physical device to be controlled by a particular device object. Theswitch statement selects a particular concrete derived device class foreach device ID retrieved from the device table. CreateDeviceList( )stores references to each device object in the device list with“aDeviceList.add( ).” CreateDeviceList( ) returns a reference to thedevice list with “return aDeviceList.”

The class diagram of FIG. 3 includes an exemplary device class (214).The exemplary device class (214) of FIG. 3 includes a deviceID field(472) uniquely identifying the physical device to be administered by theexecution of the action. The exemplary device class (214) of FIG. 3includes an address field (480) identifying a location of a physicaldevice on a data communications network. The exemplary device class(214) of FIG. 3 provides a communications field (478) for a reference toan instance of a communications class that implements a datacommunications protocol to effect communications between an instance ofa device class and a physical device.

The device class of FIG. 3 includes an attribute field (481) containinga value of current attribute of the device. An example of a currentattribute of a device is an indication that the device is “on” or “off.”Other examples of current attributes include values indicating aparticular setting of a device. The device class of FIG. 3 also includesaccessor methods (474, 476) for getting and setting attributes of aphysical device. While the exemplary device class of FIG. 3 includesonly one attribute field and accessor methods for getting and settingthat attribute, many device classes useful in implementing methods ofthe present invention can support more than one attribute. Such classescan also include an attribute ID field and accessor methods for gettingand setting each attribute the device class supports.

The exemplary class diagram of FIG. 3 includes a communications serviceclass (219). The communications service class (219) provides a factorymethod named createCommsObject(deviceID, networkAddress) (574) thatinstantiates a communications object that implements a datacommunications protocol to effect communications between an instance ofa device class and a physical device. The createCommsObject( ) method(574) finds a communications class ID in a communications class recordin a communication class table having a device ID that matches its callparameter. In many embodiments, the createCommsObject( ) method (574)then instantiates a particular concrete derived communications classidentified through a switch statement as described above, passing to theconstructor the networkAddress from its parameter list, so that the newcommunications object knows the address on the network to which the newobject is to conduct data communications. Each concrete derivedcommunications class is designed to implement data communicationsaccording to a particular data communications protocol, Bluetooth,802.11b, Lonworks, X-10, and so on.

Class diagram of FIG. 3 includes an exemplary communications base class(215). In typical embodiments, at least one concrete communicationsclass is derived from the base class for each data communicationsprotocol to be supported by a particular DML. Each concretecommunications class implements a particular data communicationsprotocol for communications device objects and physical devices. Eachconcrete communications class implements a particular datacommunications protocol by overriding interface methods (482, 484) toimplement actual data communications according to a protocol.

Communications classes allow device classes (214) to operateindependently with respect to specific protocols required forcommunications with various physical devices. For example, one light ina user's home may communicate using the LonWorks protocol, while anotherlight in the user's home may communicate using the X-10 protocol. Bothlights can be controlled by device objects of the same device classusing communications objects of different communications classes, oneimplementing LonWorks, the other implementing X-10. Both device objectscontrol the lights through calls to the same communications classinterface methods, send( ) (482) and receive( ) (484), neither knowingnor caring that in fact their communications objects use differentprotocols.

FIG. 4 is a class relationship diagram illustrating an exemplaryrelationship among the exemplary classes of FIG. 3. In the classrelationship diagram of FIG. 4, the solid arrows representinstantiation. The solid arrow points from the instantiating class tothe instantiated class. In the class relationship diagram of FIG. 4, thedotted arrows represent references. The arrow points from a referencedclass to a class whose objects possesses references to the referencedclass. That is, an object-oriented relation of composition, a “has-a”relationship between classes, is shown by an arrow with a dotted line.

The exemplary class relationship diagram of FIG. 4 includes a DML class(202). A DML object of the DML class (202) instantiates an object of themetric service class (204), an object of the metric vector service class(207), and an object of the metric space service class (209). The DMLobject also instantiates an object of the metric range service class(208) an object of the action service class (217), and an object of thedynamic action list service class (211). The DML object alsoinstantiates an object of the device service class (218) and an objectof the communications service class (219).

When the DML receives a metric (200) from a metric sensor, the DML usesa call such as:Metric aMetric=MetricService.createMetricObject(userID, metricID,metricValue)causing the metric service (204) to instantiate an object of the metricclass (206). The metric service passes a reference to metric object(206) to metric vector service object (207). The metric object containsa reference to an object of the action service class (217) and a metricaction list (622).

As shown in the class relationship diagram of FIG. 4, a metric vectorservice (207) instantiates an object of the metric vector class (606).In many embodiments, the metric vector service class receives areference to a metric object and using a parameterized factory method,such as createMetricVectorObject( ), instantiates a metric vectorobject. As shown in the class relationship diagram of FIG. 4, an objectof the metric vector class (606) contains a reference to an object ofthe metric class (206), an object of the metric space service class(209), an object of the metric space class (610), an object of thedynamic action list service class (211) and a dynamic action list (212).

As shown in the class relationship diagram of FIG. 4, a metric spaceservice (209) instantiates an object of the metric space class (610). Inmany example embodiments, a metric space service uses a parameterizedfactory method, such as createMetricSpace( ), to instantiate a metricspace object. The metric space service passes a reference to the metricspace object (610) to the metric vector object. The metric space object(610) contains a reference to objects of the metric range class (210).

As shown in the class relationship diagram of FIG. 4, the metric rangeservice (208) instantiates an object of the metric range class (210). Inmany examples embodiments of the present invention, the metric rangeservice (208) uses a parameterized factory method, such ascreateRangeObject( ), to instantiate the metric range (210). The metricrange service (208) passes to the metric space service (209) a referenceto the metric range (210).

As shown in the class relationship diagram of FIG. 4, a action service(217) instantiates a metric action list (622) and objects of actionclasses (216). The metric action list (622) is instantiated withreferences to each of the instantiated actions (216). Each action (216)is instantiated with a reference to the device service (218). In typicalexamples of methods according to the present invention, the actionservice (217) uses a parameterized factory method, such ascreateActionList( ), to instantiate a metric action list (622) andinstantiate actions (216). The action service (217) passes, to themetric (206), a reference to the metric action list (622).

As shown in FIG. 4, the dynamic action list service (211) instantiates adynamic action list (626) and passes a reference to the dynamic actionlist (626) to calling methods in the metric vector (606). In typicalexamples of methods according to the present invention, the dynamicaction list service (211) uses a method, such ascreateDynamicActionList( ) to instantiate a dynamic action list. In manyembodiments, createDynamicActionList( ) is parameterized with action IDsof metric action lists associated with user metrics that are outsidetheir corresponding metric ranges. The dynamic action list (626)possesses references to objects of the action class (216).

In the example of FIG. 4, the device service (218) instantiates a devicelist of the device list class (222) and instantiates a device object ofthe device class (214). The device list (222) is instantiated with areference to the device object (214). The device object (214) isinstantiated with a reference to the communications service (219). Intypical examples of methods according to the present invention, thedevice service (218) uses a parameterized factory method, such ascreateDeviceList( ), to instantiate a device list (222) and instantiatea device object (216). The device service (218) passes, to the action(216), a reference to the device list (222)

In the example of FIG. 4, the communications service (219) instantiatesa communications object of the communications class (215). In typicalexamples of the methods according to the present invention, thecommunications service (219) uses a parameterized factory method, suchas createCommsObject( ), to instantiate a communications object (215).The communications service (219) passes, to the device object (214), areference to the communications object (215).

FIG. 5 is a class relationship diagram illustrating an exemplaryrelationship between some of the classes of FIG. 3. In the example ofFIG. 5, an objection of the DML class (202) instantiates an object ofthe relational metric service class (684). The relational metric serviceclass has a reference to user metrics (206) available in metric cache.

The relational metric service class (684) instantiates an object of therelational metric class (664) in dependence upon the user metrics inmetric cache, or selects a pre-created relational metrics in dependenceupon the user metrics in metric cache. The relational metric has areference to a metric action list (622). The metric vector receives,from the relational metric service, a reference to the relational metric(664).

Administering Devices in Dependence upon User Metrics

FIG. 6 is a data flow diagram illustrating an exemplary method foradministering devices. The method of FIG. 6 includes receiving (302) auser metric (206). As mentioned above, a “user metric” comprises datadescribing an indication of user condition. An “indication of a user'scondition” is a quantifiable aspect of a user's condition and a quantitymeasuring the aspect. Examples of quantifiable aspects of a user'scondition include body temperature, heart rate, blood pressure,location, galvanic skin response, or any other aspect of user conditionas will occur to those of skill in the art.

In typical embodiments of the present invention, a user metric isimplemented as a user metric data structure or record (206), such as theexemplary user metric (206) of FIG. 6. The user metric of FIG. 6includes a userID field (405) identifying the user whose indication ofcondition is represented by the metric. The user metric (206) of FIG. 6also includes a metric ID field (407) identifying the aspect of usercondition the metric represents, such as, for example, blood pressure,heart rate, location, or galvanic skin response. The user metric (204)also includes a value field (409) containing the value of the aspect ofthe user's condition that the metric represents. An example of a valueof a metric is a body temperature of 100° Fahrenheit.

In many embodiments of the method of FIG. 6, receiving (302) a usermetric includes receiving a user metric from a metric sensor (406). Insome examples of the method of FIG. 6, the metric sensor (406) reads anindication of a user's condition, creates a user metric in dependenceupon the indication of a user's condition, and transmits the user metricto a DML In many embodiments, the metric sensor transmits the usermetric to the DML in a predefined data structure, such as the metric(206) of FIG. 6, to the DML using, for example, protocols such asBluetooth, 802.11, HTTP, WAP, or any other protocol that will occur tothose of skill in the art.

In the method of FIG. 6, receiving (302) a user metric includesreceiving a user metric into metric cache memory (305). That is, a usermetric is received by a DML and then stored in cache. In manyembodiments of the method of FIG. 6, metric cache memory (305) is cachememory available to a DML to facilitate carrying out steps ofadministering devices in accordance with the present invention.

The method of FIG. 6 includes determining (306) whether a value of theuser metric is outside (309) of a predefined metric range. A predefinedmetric range includes a predetermined range of values for a given metricID for a particular user. In many embodiments of the method of FIG. 6,the predefined metric range is designed as a range of typical or normalmetrics values for a user. One example of a predefined metric range is arange of metric values representing a resting heart rate of 65-85 beatsper minute.

In many examples of the method of FIG. 6, a predefined metric range fora user is implemented as a data structure or record such as the metricrange (210) of FIG. 6. The metric range of FIG. 6 includes a metric IDfield (462) identifying the kind of user metrics. The metric range ofFIG. 6 includes a user ID field (464) identifying the user for whom themetric range represents a range of metric values. The metric range ofFIG. 6, for example, includes a Max field (468) representing the maximummetric value of the metric range and a Min field (470) representing theminimum metric value of the metric range. That is, in typicalembodiments, it is a maximum and minimum metric value in a range thatdefines a value range for the metric.

In many embodiments, determining (306) that the value of the user metric(206) is outside (309) of a predefined metric range includes comparingthe metric value of a user metric with the maximum and minimum valuesfrom a metric range for that metric and for the same user. In manyexamples of the method of FIG. 6, determining that a user metric isoutside a predefined metric range also includes determining that themetric value (409) of the user metric (206) is either greater than themaximum value (468) of the metric range (210) or below the minimum value(470) of the range in the metric range (210). A user metric of metric IDidentifying the metric as ‘heart rate’ having, for example, a metricvalue of 100 beats per minute is outside the exemplary metric range forresting heart rate of 65-85 beats per minute.

If the value of the user metric is outside the metric range, the methodof FIG. 6 includes identifying (310) an action in dependence upon theuser metric. An action includes one or more computer programs,subroutines, or member methods that when executed, control one or moredevices. Actions are typically implemented as object oriented classesand manipulated as objects or references to objects. In fact, in thisspecification, unless context indicates otherwise, the terms ‘action,’‘action object,’ and ‘reference to an action object’ are treated more orless as synonyms. In many embodiments of the method of FIG. 6, an actionobject calls member methods in a device class to affect currentattributes of the physical device. In many embodiments of the method ofFIG. 6, action classes or action objects are deployed in OSGi bundles toa DML on a services gateway.

In the method of FIG. 6, identifying (310) an action includes retrieving(365) an action ID (315) from a metric action list (622) organized byuser ID and metric ID. In the method of FIG. 6, retrieving an action IDfrom a metric action list includes retrieving from a list theidentification of the action (the ‘action ID’) to be executed when avalue of a metric of a particular metric ID and for a particular user isoutside the user's predetermined metric range. The action list can beimplemented, for example, as a Java list container, as a table in randomaccess memory, as a SQL database table with storage on a hard drive orCD ROM, and in other ways as will occur to those of skill in the art.

As mentioned above, the actions themselves comprise software, and so canbe implemented as concrete action classes embodied, for example, in aJava package imported into the DML at compile time and therefore alwaysavailable during DML run time. Executing (314) an action (312) thereforeis often carried out in such embodiments by use of a switch( ) statementin the DML. Such a switch( ) statement can be operated in dependenceupon the action ID and implemented, for example, as illustrated by thefollowing segment of pseudocode: switch (actionID) {     Case 1:actionNumber1.take_action( ); break;     Case 2:actionNumber2.take_action( ); break;     Case 3:actionNumber3.take_action( ); break;     Case 4:actionNumber4.take_action( ); break;     Case 5:actionNumber5.take_action( ); break;     // and so on } // end switch( )

The exemplary switch statement selects a particular device controllingobject for execution depending on the action ID. The device controllingobjects administered by the switch( ) in this example are concreteaction classes named actionNumber1, actionNumber2, and so on, eachhaving an executable member method named ‘take_action( ),’ which carriesout the actual work implemented by each action class.

Executing (314) an action (312) also is often carried out in suchembodiments by use of a hash table in the DML. Such a hash table canstore references to action object keyed by action ID, as shown in thefollowing pseudocode example. This example begins by an action service'screating a hashtable of actions, references to objects of concreteaction classes associated with a particular metric ID, using action IDsas keys. In many embodiments it is an action service that creates such ahashtable, fills it with references to action objects pertinent to aparticular metric ID, and returns a reference to the hashtable to acalling metric object. Hashtable ActionHashTable = new Hashtable( );ActionHashTable.put(“1”, new Action1( )); ActionHashTable.put(“2”, newAction2( )); ActionHashTable.put(“3”, new Action3( ));

Executing a particular action then can be carried out according to thefollowing pseudocode: Action anAction = (Action)ActionHashTable.get(“2”); if (anAction != null) anAction.take_action( );

Many examples in this specification are described as implemented withlists, often with lists of actions, for example, returned with areference to a list from an action service, for example. Lists oftenfunction in fashion similar to hashtables. Executing a particularaction, for example, can be carried out according to the followingpseudocode: List ActionList = new List( ); ActionList.add(1, newAction1( )); ActionList.add(2, new Action2( )); ActionList.add(3, newAction3( ));

Executing a particular action then can be carried out according to thefollowing pseudocode: Action anAction = (Action) ActionList.get(2); if(anAction != null) anAction.take_action( );

The three examples just above use switch statements, hash tables, andlist objects to explain executing actions according to embodiments ofthe present invention. The use of switch statements, hash tables, andlist objects in these examples are for explanation, not for limitation.In fact, there are many ways of executing actions according toembodiments of the present invention, as will occur to those of skill inthe art, and all such ways are well within the scope of the presentinvention.

FIG. 7 sets forth a data flow diagram illustrating an exemplary methodof executing an action. In the method of FIG. 7, executing an actionincludes identifying (380) a device class (214) representing a physicaldevice (316) administered by the action. Typical device classes includemember methods for administering the device. Typical member methods foradministering the device include member methods for getting and settingvalues of device attributes in physical devices. In the case of a lampsupporting multiple settings for light intensity, for example, a membermethod get( ) in a device class can gets from the lamp a value for lightintensity, and a member method set( ) in a device class sets the lightintensity for the lamp.

In the method of FIG. 7, executing an action includes identifying (384)a communication class (215) for the physical device (316). Tocommunicate the member methods of the device class to the physicaldevice, a communications class implements a protocol for communicatingwith a physical device. Typical communications classes include membermethods that construct, transmit, and receive data communicationsmessages in accordance with the protocol implemented by a communicationclass. The member methods in a communication class transmit and receivedata communications messages to and from a physical device. Acommunications class advantageously separates the protocols used tocommunicate with the physical device from the actions to be effected onthe device, so that a device class interface comprising get( ) and set() methods, for example, can usefully communicate with a physical deviceby use of any data communications protocol with no need to reprogram thedevice class and no need to provide one device class for eachcombination of physical device and protocol.

For further explanation, consider the following brief use case. A user'smetric sensor reads the user's heart rate at 100 beats per minute, andcreates a metric for the user having a user ID identifying the user, ametric ID identifying the metric as “heart rate,” and a metric value of100. The metric sensor transmits the user metric to the DML through aservices gateway. The DML receives the user metric and compares the usermetric with the user' metric range for resting heart rates having arange of 65-85. The DML determines that the user metric is outside thepredefined metric range. The DML uses the user ID and the metric ID toretrieve from a list an action ID for a predefined action to be executedin response to the determination that the value of the user's heart ratemetric value is outside the user's metric range for heart rate. The DMLfinds a device controlling-action ID identifying an action object havinga class name of ‘someAction,’ for example, and also having an interfacemember method known to the DML, such as the take_action ( ) methoddescribed above in the switch( ) statement.

In this example, the DML effects the action so identified by callingsomeAction.take_action( ). The take_action( ) method in this example isprogrammed to call a device service for a list of references to deviceobjects representingphysical devices whose attributes are to be affectedby the action. The device service is programmed with a switch( )statement to create in dependence upon the action ID a list ofreferences to device objects and return the device list to the callingaction object, or rather, to the calling take_action( ) method in theaction object.

In creating the device list, the device service is programmed toinstantiate each device having a reference entered in the list, passingas a constructor parameter a reference to a communications service. Eachdevice so instantiated has a constructor programmed to call aparameterized factory method in the communications service, passing as aparameter an identification of the calling device object. Thecommunications service then instantiates and returns to the device areference to a communication object for the communications protocolneeded for that device object to communicate with its correspondingphysical device.

The principal control logic for carrying out an action typically, inembodiments of the present invention, resides in the principal interfacemethod of an action class and objects instantiated from it. In thisexample, the take_action( ) method is programmed to carry out a sequenceof controlling method calls to carry out the changes on the physicaldevices that this action class was developed to do in the first place.The take_action( ) method carries out this work with a series of callsto accessor methods (set( ) and get( ) methods) in the device objects inits device list.

FIG. 8 is a data flow diagram illustrating an exemplary method ofdetermining (306) that the user metric (206) is outside the predefinedmetric range (210). In many embodiments of methods for administeringdevices, the user metric (206) is represented in data as a datastructure or record, such as the user metric record of FIG. 8. The usermetric (206) includes a user ID field (405), a metric ID field (407),and a value field (409).

In the example of FIG. 8, a predefined metric range for a metric isrepresented in data as a metric range such as the metric range (210) ofFIG. 8. The exemplary metric range (210) sets forth a maximum rangevalue (468) and a minimum range value (470) for a particular user for aparticular metric. The particular user and the particular metric for theexemplary range are identified respectively in a user ID field (464) anda metric ID field (462).

In the method of FIG. 8, determining (306) that value of the user metric(206) is outside (309) of a predefined metric range (210) includesmeasuring (502) a degree (504) to which the user metric (206) is outside(309) the predefined metric range (210). In many embodiments of thepresent invention, measuring (502) the degree (504) to which the usermetric (206) is outside (309) the metric range (210) includesidentifying the magnitude by which the value of the user metric isgreater than the maximum metric value the metric range or the magnitudeby which the value of the user metric value is less than the minimumvalue of the predefined metric range. To the extent that measuring thedegree to which a metric is out of range includes identifying a measureas greater than a maximum range value or less than a minimum rangevalue, the measurement often advantageously includes both a magnitudeand an indication of direction, such as, for example, a sign (+ or −),an enumerated indication such as, for example, ‘UP’ or ‘DOWN’, or aBoolean indication such as true for high and false for low.

In the method of FIG. 8, identifying (310) an action in dependence uponthe user metric includes identifying (512) an action in dependence uponthe degree (504) to which the value of the user metric (206) is outside(309) the metric range and also often in dependence upon the directionin which the metric is out of range. In many embodiments of the methodof FIG. 8, identifying (512) the action in dependence upon the degree(504) to which the user metric is outside the predefined metric rangeincludes retrieving an action ID from a metric action list (622)organized by metric ID, user ID, degree, and direction.

In many DMLs according to the present invention are preinstalled deviceclasses for all of the devices the DML supports. Newly acquired physicaldevices identify themselves as being on the network and the DMLassociates the device ID with the device class already installed on theDML. In such an example embodiment, the DML identifies the device byassociating the device ID with the pre-installed device class.

Administering Devices in Dependence Upon User Metric Vectors IncludingRelational Metrics and Location Based Device Control

FIG. 9 is a data flow diagram illustrating a method for administeringdevices in accordance with the present invention. The method of FIG. 9includes receiving (660) a plurality of user metrics (206). In manyembodiments of the method of FIG. 9, receiving (660) a plurality ofdisparate user metrics (206) includes receiving disparate user metricsfrom one or more metric sensors (406). The term ‘disparate’ user metricsmeans user metrics of different kinds. That is, user metrics ofdifferent kinds typically also having different metric values.

In some examples of the method of FIG. 9, a metric sensor (406) reads anindication of a user's condition, creates a user metric in dependenceupon the indication of a user's condition, and transmits the user metricto a DML In many examples, the metric sensor transmits the user metricto the DML in a predefined data structure, such as the metric (206) ofFIG. 3, to the DML using, for example, protocols such as Bluetooth,802.11, HTTP, WAP, or any other protocol that will occur to those ofskill in the art.

The method of FIG. 9 includes creating (662) a relational metric (664)in dependence upon a plurality of user metrics (206). In many examplesof the method of FIG. 9, a relational metric (664) is a data structurerepresenting specific indication of user condition derived in dependenceupon a plurality of user metrics, or created in anticipation of usermetrics that will be received in the future. That is, in some examplesof the method of FIG. 9, a relational metric is a metric created independence upon a plurality of user metrics in metric cache. Forexample, a relational metric for “moving” can be created from at leasttwo other metrics for location. In other examples of the method of FIG.9, a relational metric is pre-created in anticipation of user metricsthat will be received in metric cache. In many of these examples, thepre-created relation metric is selected for the user when the usermetrics in metric cache match a set of predefined metrics that make up apredefined metric pattern. Examples of relational metrics includemetrics representing user movement, no user movement, a turn, speeds oftravel, biometric values rising, biometric values falling, the rate ofchange of biometric values, or any other relationship that will occur tothose of skill in the art.

A relational metric often provides information about a user's conditionnot available in a single received user metric. A single received usermetric having a metric value often indicates only the current value ofthat metric. Said differently, a single user metric often provides asnapshot of a single aspect of user condition. A relational metric, onthe other hand, often provides further information about the user'scondition such as how a user's metrics are changing, responding toexecuted actions, or other information that will occur to those of skillin the art.

In many examples of the method of FIG. 9, creating a relational metric(664) in dependence upon a plurality of user metrics (206) includescalling member methods in a relational metric service, such as forexample, createRelationalMetric( ) (686 on FIG. 3). In some examples ofthe method of FIG. 9, createRelationalMetric( ) (686) determines arelationship among the user metrics in metric cache and instantiates theappropriate relational metric. In other embodiments,createRelationalMetric( ) compares the user metrics in metric cache witha set of predefined metrics that together make-up a predefined metricpattern. If the user metrics in metric cache match the predefinedmetrics making up the predefined metric pattern, createRelationalMetric() retrieves an appropriate pre-created relational metric from arelational metric database.

The method of FIG. 9 includes creating (604) a user metric vector (606)comprising at least one user metric (206) and at least one relationalmetric (664). A user metric vector comprised of at least one user metric(206) and at least one relational metric (664) represents a complexindication of user condition having multiple quantifiable aspects of auser's condition and multiple quantities measuring the aspects. That is,a user metric vector is typically a collection of a user metrics eachrepresenting a single quantifiable aspect of a user's condition and aquantity measuring the aspect. In the method of FIG. 9, a user metricvector also includes at least one relational metric identifying arelationship among at least two received user metrics.

In typical embodiments of the present invention, a user metric vector isimplemented as a user metric vector data structure or record, such asthe exemplary user metric vector (606) discussed above with reference toFIG. 3. The user metric vector (606) includes a user ID (405 on FIG. 3)identifying the user and a metric vector ID (408 on FIG. 3) uniquelyidentifying the user metric vector. The user metric vector (606) alsoincludes data storage for a metric list (652 on FIG. 3) containingreferences to user metrics. The user metric vector (606) also includesdata storage for a relational metric list (653 on FIG. 3) containingreferences to relational metrics.

The method of FIG. 9 includes creating (605) a user metric space (610)comprising a plurality of metric ranges (210). A user metric space (610)is comprised of a plurality of disparate metric ranges for a user. Thatis, a metric space is defined by a plurality of disparate metric rangesfor a plurality of disparate metric IDs. In many examples of the methodof FIG. 9, the metric ranges of the user metric space represent normalor comfortable ranges in metric value for given a user metric for agiven user. In many examples of the method of FIG. 9, the user metricspace also includes metric ranges for the relational metrics of the usermetric vector. In many exemplary embodiments of the present invention, ametric space is implemented as a metric space data structure such as theexemplary metric space (610) of FIG. 3 including a user ID and datastorage (655) for a list of references to disparate metric ranges for auser.

The method of FIG. 9 includes determining (608) whether the user metricvector (606) is outside (309) the user metric space (610). In variousalternative example embodiments determining (608) whether the usermetric vector (606) is outside (309) a user metric space (610) iscarried out using different methods. Methods of determining whether theuser metric vector (606) is outside (309) a user metric space (610)range in complexity from relatively straight forward comparison of theuser metrics and relational metrics of the metric vector with theircorresponding metric ranges of the metric space to more complexalgorithms. Exemplary methods of determining (608) whether the usermetric vector (606) is outside (309) a user metric space (610) aredescribed in more detail below with reference to FIG. 13.

If the user metric vector (606) is outside (309) a user metric space(610), the method of FIG. 9 includes, identifying (630) an action (315).An action typically includes one or more computer programs, subroutines,or member methods that when executed, control one or more devices.Actions are typically implemented as object oriented classes andmanipulated as objects or references to objects. In fact, in thisspecification, unless context indicates otherwise, the terms ‘action,’‘action object,’ and ‘reference to an action object’ are treated more orless as synonyms. In many examples of the method of FIG. 9, an actionobject calls member methods in a device class to affect currentattributes of the physical device. In many examples of the method ofFIG. 9, action classes or action objects are deployed in OSGi bundles toa DML on a services gateway.

In many examples of the method of FIG. 9, identifying (630) an action(315) includes creating (624), in dependence upon the user metric vector(606), a dynamic action list (626). In many examples of the method ofFIG. 9, a dynamic action list is a list of action IDs created independence upon metric action lists that are associated with theparticular metrics of the user metric vector that are outside theircorresponding metric ranges of the user metric space. That is, eachmetric of the metric vector that is outside its corresponding metricrange has an associated metric action list. The associated metric actionlist includes action IDs for execution when its associated metric isoutside its corresponding metric range. A dynamic action list is anaction list including action IDs identified in dependence upon thosemetric action lists associated with the particular metrics of a usermetric vector outside their corresponding metric ranges of the usermetric space. A dynamic action list advantageously provides a list ofaction IDs tailored to the user's current condition.

In many example embodiments of the present invention, creating a dynamicaction list includes calling member methods in a dynamic action serviceobject. In many examples of the method of FIG. 9, creating a dynamicaction list includes parameterizing a member method, such ascreateDynamicActionList( ), with action IDs retrieved from action listsassociated with the particular user metrics of the user metric vectorthat are outside their corresponding metric ranges of the user metricspace. In many examples of the method of FIG. 9,createDynamicActionList( ) returns to its caller in the user metricvector a dynamic action list including action IDs identified independence upon the action IDs contained in metric action lists. Invarious alternative examples of the method of FIG. 9, a dynamic actionlist can be implemented, for example, as a hashtable, Java listcontainer, as a table in random access memory, as a SQL database tablewith storage on a hard drive or CD ROM, and in other ways as will occurto those of skill in the art.

The method of FIG. 9 includes executing the action (614). Executing anaction therefore is often carried out in such embodiments by use of aswitch( ) statement in the DML. Such a switch( ) statement can beoperated in dependence upon the action ID and implemented, for example,as illustrated by the following segment of pseudocode: switch (actionID){     Case 1: actionNumber1.take_action( ); break;     Case 2:actionNumber2.take_action( ); break;     Case 3:actionNumber3.take_action( ); break;     Case 4:actionNumber4.take_action( ); break;     Case 5:actionNumber5.take_action( ); break;     // and so on } // end switch( )

The exemplary switch statement selects a particular device controllingobject for execution depending on the action ID. The device controllingobjects administered by the switch( ) in this example are concreteaction classes named actionNumber1, actionNumber2, and so on, eachhaving an executable member method named ‘take_action( ),’ which carriesout the actual work implemented by each action class.

In many examples of the method of FIG. 9, executing an action is carriedout by use of a hash table in a DML. Such a hash table stores referencesto action object keyed by action ID, as shown in the followingpseudocode example. This example begins by a dynamic action listservice's creating a hashtable of actions, references to objects ofconcrete action classes associated with a particular metric ID, usingaction IDs as keys. In many embodiments it is a dynamic action listservice that creates such a hashtable, fills it with references toaction objects pertinent to a particular metric ID of the user metricvector outside its corresponding metric range of the user metric space,and returns a reference to the hashtable to a calling vector object.Hashtable DynamicActionHashTable = new Hashtable( );DynamicActionHashTable.put(“1”, new Action1( ));DynamicActionHashTable.put(“2”, new Action2( ));DynamicActionHashTable.put(“3”, new Action3( ));

Executing a particular action then can be carried out according to thefollowing pseudocode: Action anAction = DynamicActionHashTable.get(“2”);if (anAction != null) anAction.take_action( );

Many examples of the method of FIG. 9 are also implemented through theuse of lists. Lists often function in fashion similar to hashtables.Building such a list can be carried out according to the followingpseudocode: List DynamicActionList = new List( );DynamicActionList.add(1, new Action1( )); DynamicActionList.add(2, newAction2( )); DynamicActionList.add(3, new Action3( ));

Executing a particular action then can be carried out according to thefollowing pseudocode: Action anAction = DynamicActionList.get(2); if(anAction != null) anAction.take_action( );

The three examples just above use switch statements, hash tables, andlist objects to explain executing actions according to embodiments ofthe present invention. The use of switch statements, hash tables, andlist objects in these examples are for explanation, not for limitation.In fact, there are many ways of executing actions according toembodiments of the present invention, as will occur to those of skill inthe art, and all such ways are well within the scope of the presentinvention.

In some examples of the method of FIG. 9, executing an action includesidentifying a device class for the device. Typical device classesinclude member methods for administering the device. Typical membermethods for administering the device include member methods for gettingand setting values of device attributes in physical devices. In the caseof a lamp supporting multiple settings for light intensity, for example,a member method get( ) in a device class can gets from the lamp a valuefor light intensity, and a member method set( ) in a device class setsthe light intensity for the lamp.

In many examples of the method of FIG. 9, executing an action includesidentifying a communications class for the device. To communicate themember methods of the device class to the physical device, acommunications class implements a protocol for communicating with aphysical device. Typical communications classes include member methodsthat construct, transmit, and receive data communications messages inaccordance with the protocol implemented by a communication class. Themember methods in a communication class transmit and receive datacommunications messages to and from a physical device. A communicationsclass advantageously separates the protocols used to communicate withthe physical device from the actions effecting the device, so that adevice class interface comprising get( ) and set( ) methods, forexample, can usefully communicate with a physical device by use of anydata communications protocol with no need to reprogram the device classand no need to provide one device class for each combination of physicaldevice and protocol.

FIG. 10 is a data flow diagram illustrating an exemplary method ofcreating (662) a relational metric (664) in dependence upon theplurality of user metrics (206). As discussed above, in some examples ofthe method of FIG. 10, a relational metric is a metric created independence upon received user metrics in metric cache. In the method ofFIG. 10, creating (662) a relational metric (664) in dependence upon theplurality of user metrics (206) includes filtering (665) the usermetrics. In many examples of the method of FIG. 10, filtering the usermetrics includes identifying the metric IDs of the received user metricsin metric cache and sorting the user metrics by metric ID.

FIG. 10 illustrates only two resultant filtered user metrics (206A,206B). In many examples of the method of FIG. 10 however, filtering theuser metrics results in many filtered user metrics stored in cache andused to create a relational metric. In various examples of the method ofFIG. 10, how many filtered user metric maintained in metric cache willvary according to factors such as the metric ID of the filtered usermetric, the types of relational metrics created in dependence upon thefiltered user metrics, or any other factor that will occur to those ofskill in the art. A relational metric for “user movement,” for example,may be created from only two filtered user metrics, while a relationalmetric for “user moving in a circle” may require more than two filtereduser metrics for location in metric cache.

In the method of FIG. 10, creating (662) a relational metric (664) independence upon the plurality of user metrics (206A, 206 B) includesdetermining (666) a relationship (668) between a first filtered usermetric (206 A) and a second filtered user metric (206 B). In the methodof FIG. 10, determining (666) a relationship (668) between a firstfiltered user metric (206 A) and a second filtered user metric (206 B)includes comparing (670) the first filtered user metric (206 A) with thesecond filtered user metric (206 B). In many examples of the method ofFIG. 11, comparing the first filtered user metric with the secondfiltered user metric to determine a relationship is carried outalgorithmically. That is, for example, in terms of computer programcoding, determining relationships among user metrics is carried out byuse of switch statements or sequences of if-then-else statementimplementing logic similar to that illustrated for example as follows:

-   -   If a first user metric represents location 1        -   If a second user metric represents location 2            -   If location 1 is not equal to location 2                -   Then create a relational metric object representing                    the relationship of ‘in motion.’                    Or    -   If a first user metric represents location L1 at time t1        -   If a second user metric represents location L2 at time t2        -   If location L1 is not equal to location L2            -   Then                -   Calculate speed S and direction D            -   and                -   create a relational metric object representing the                    relationship of ‘in motion’ with value fields for                    speed set to S and direction set to D

In many examples of the method of FIG. 11, determining a relationship independence upon the user metric is not limited to comparing only twouser metrics. As an example of comparing more than two user metrics,consider the following example of algorithmic logic for determining therelationship ‘turned right.’

-   If a first user metric represents location L1 at time t1    -   If a second user metric represents location L2 at time t2        -   If a third user metric represents location L3 at time t3            -   If L1<>L2<>L3            -   Then                -   Calculate direction D1 from L1 and L2                -   Calculate direction D2 from L2 and L3                -   If D1-D2 is approximately 90 degrees                -   Then                -   create a relational metric representing                -   the relationship of ‘turned right.’

In the method of FIG. 10, creating (662) a relational metric (664) independence upon the plurality of user metrics (206A, 206 B) includesdetermining (672) a magnitude (674) of the relationship (668) betweenthe first filtered user metric (206A) and the second filtered usermetric (206B). In many examples of the method of FIG. 10, the determinedmagnitude is included as the value of the created relational metric. Insome examples of the method of FIG. 10, determining (672) a magnitude(674) of the relationship (668) between the first filtered user metric(206A) and the second filtered user metric (206B) includes subtracting(676) the value of the second filtered user metric (206B) from the valueof the first filtered user metric (206 A). In other alternative examplesof the method of FIG. 10, determining (672) a magnitude (674) of therelationship (668) between the first filtered user metric (206A) and thesecond filtered user metric (206B) includes adding the first filtereduser metric and the second filtered user metric, or applying any otherfunction or algorithm to the first filtered user metric and the secondfiltered user metric that will occur to those of skill in the art.

FIG. 11 is a data flow diagram illustrating an exemplary method ofcreating (662) a relational metric (664) in dependence upon theplurality of user metrics (206). In the method of FIG. 11, creating(662) a relational metric (664) in dependence upon the plurality of usermetrics (206) includes determining (678) whether the plurality of usermetrics (206) match (681) a predefined metric pattern (663). In manyexamples of the method of FIG. 11, a predefined metric pattern includesa set of pre-created user metrics that have been predetermined to makeup a particular pattern of metrics demonstrating a predefinedrelationship.

In many examples of the method of FIG. 11, determining (678) whether theplurality of user metrics (206) match (681) a predefined metric pattern(663) includes comparing (679) a plurality of user metrics in metriccache with a set of predefined metrics that make up a predefined metricpattern (663). In many examples of the method of FIG. 11, comparing theuser metrics in metric cache with the predefined metric patterns in therelational metric database includes comparing the value of the usermetrics with the values of the individual predefined metrics includedwithin the predefined metric pattern and comparing the metric IDs of theuser metrics in metric cache with the metric IDs of the individualpredefined metrics included within the predefined metric pattern. Inmany examples of the method of FIG. 11, a predefined metric pattern mayinclude predefined metrics of different kinds that together identify ametric pattern.

The plurality of user metrics in metric cache do not have to be exactlythe same as the set of predefined metrics that make up the predefinedmetric patterns to be considered a match. The degree to which the usermetrics in metric cache must be the same as the predefined metrics ofthe predefined metric pattern to be considered a match depends ofvarious factors such as the tolerances of the methods used for comparingtype of information contained in the user metrics and the predefinedmetrics, the accuracy and precision used in generating the user metricsand the predefined metrics, and other factors that will occur to thoseskilled in the art.

In the method of FIG. 11, the predefined metric patterns are stored in ametric pattern table (680). In many examples of method of FIG. 11, themetric pattern table includes sets of predetermined metrics that make uppredefined metric patterns indexed by for example metric ID for therelational metric that they identify. In many examples of the method ofFIG. 11, the user metrics in metric cache are compared with sets ofpredetermined metrics that make up the predefined metric pattern. If theuser metrics match the set of predetermined metrics making up thepredefined metric pattern, a metric ID is identified for a relationalmetric.

In the method of FIG. 11, creating (662) a relational metric (664) independence upon the plurality of user metrics (206) includes retrieving(683) a relational metric (664). In many examples of the method of FIG.11, the relational metric is retrieved from a relation metric table(665) in dependence upon a metric ID identified by comparing the usermetrics in metric cache with the predefined metric patterns stored inthe metric pattern table.

FIG. 12 is a data flow diagram illustrating an exemplary method ofcreating (604) a user metric vector (606) and an exemplary method ofcreating (605) a user metric space (610). In the method of FIG. 12,creating (604) a user metric vector (606) comprising at least one usermetric (206) and at least one relational metric (664) comprisesassociating (603) at least one user metric with the user metric vectorand associating (682) at least one relational metric (664) with the usermetric vector (606). ‘Associated,’ generally in this disclosure andsubject to context, means associated by reference. That is, saying thatan object of one class is associated with another object means that thesecond object possesses a reference to the first. The objects can bemutually associated, each possessing a reference to the other. Otherrelations among objects, aggregation, composition, and so on, areusually types of association, and the use of any of them, as well asothers as will occur to those of skill in the art, is well within thescope of the present invention. In the exemplary method of FIG. 12,associating (603) the plurality of disparate user metrics (206) with theuser metric vector (606) is carried out by providing references to aplurality of disparate metric objects in the user metric vector (606).

In the method of FIG. 12, creating (604) a user metric vector (606)comprising a plurality of disparate user metrics (206) includesassociating (620) at least one metric action list (622) with each usermetric (206). In many examples of the method of FIG. 12, a plurality ofmetric action lists are associated with each user metric of the uservector. The action IDs included in a metric action list associated witha particular metric identify actions designed to administer devices inaccordance with the particular aspect of user condition represented bythat metric. That is, a metric action list is tailored to affecting theuser condition represented by the user metric or relational metric. Forexample, a metric list associated with a body temperature metric mayinclude actions that administer devices such as an air conditioner, afan, a heater, automated window shades and the like.

In many examples of the method of FIG. 12, creating a user metric vectorincludes associating a plurality of metric action lists with a singleuser metric. Some such examples of the method of FIG. 12 includeassociating one metric action list with the user metric including actionIDs for execution when the value of the user metric is above itscorresponding metric range and another metric action list includingaction IDs for execution when the value of the user metric is below itscorresponding metric range. Some examples of the method of FIG. 12 alsoinclude associating metric action lists with a user metric that includeaction IDs for execution in dependence upon the degree and directionthat the user metric is outside its corresponding metric range.

In the method of FIG. 12, creating (604) a user metric vector (606)comprising a plurality of disparate user metrics (206) includesassociating (683) at least one metric action list (622) with eachrelational metric (664). In many examples of the method of FIG. 12, aplurality of metric action lists are associated with each relationalmetric of the user vector. The action IDs included in a metric actionlist associated with a particular relational metric identify actionsdesigned to administer devices in accordance with the particular aspectof user condition represented by that relational metric. That is, ametric action list is tailored to affecting the user conditionrepresented by the relational metric. For example, a metric listassociated with a body temperature metric may include actions thatadminister devices such as an air conditioner, a fan, a heater,automated window shades and the like.

In many examples of the method of FIG. 12, creating a user metric vectorincludes associating a plurality of metric action lists with a singlerelational metric. Some such examples of the method of FIG. 12 includeassociating one metric action list with the relational metric includingaction IDs for execution when the value of the relational metric isabove its corresponding metric range and another metric action listincluding action IDs for execution when the value of the relationalmetric is below its corresponding metric range. Some examples of themethod of FIG. 12 also include associating metric action lists with arelational metric that include action IDs for execution in dependenceupon the degree and direction that the user metric is outside itscorresponding metric range.

The method of FIG. 12 includes creating (605) a user metric space (610)comprising a plurality of metric ranges. In many examples of the methodof FIG. 12, a user metric space (610) is comprised of a plurality ofdisparate metric ranges that correspond in kind to the user metrics andthe relational metrics contained in the user metric vector. In manyexamples of the method of FIG. 12, the metric ranges of the user metricspace represent normal or comfortable metric ranges for the user. In themethod of FIG. 12, creating (602) a user metric space (610) includesidentifying (601) a plurality of metric ranges (210) for a plurality ofdisparate metrics (206) and associating (607) the plurality of disparatemetric ranges (210) for the plurality of disparate metrics (206) withthe user metric space (610).

In many examples of the method of FIG. 12, identifying (601) a pluralityof metric ranges (210) and associating (607) the plurality of metricranges (210) the user metric space (610) is carried out by a metricspace service that is instantiated by a DML. The metric space servicereceives, from a user metric vector, a user metric vector ID andsearches a metric space list identified by metric vector ID for a metricspace and returns to the user metric vector a metric space IDidentifying a metric space for comparison with the user metric vector.If there is no metric space for the metric vector ID, the metric spaceservice instantiates one and stores the metric space ID in the metricspace table.

FIG. 13 is a data flow diagram illustrating two exemplary methods ofdetermining (608) whether the user metric vector (606) is outside (309)a user metric space (610). The first illustrated method of determining(608) whether the user metric vector (606) is outside (309) a usermetric space (610) includes comparing (806) the metric values of theuser metrics (206) and relational metrics (664) of the user metricvector (606) with the metric ranges (210) of the metric space (610). Insome examples of the present invention, comparing a metric value of auser metric or value of the relational metric its corresponding metricrange includes measuring a degree to which the value is outside apredefined metric range and identifying if the value is above thepredefined metric range or below the predefined metric range.

In many exemplary embodiments of the present invention, determiningwhether the user metric vector is outside the metric space is a functionof multiple individual comparisons between metric values and metricranges. In various alternative embodiments of the present invention,different criteria are used to identify the number of metric values thatmust be outside their corresponding metric ranges, or the degree towhich any metric value is outside its corresponding metric range todetermine that the user metric vector is outside the metric space. Insome embodiments using a strict criteria for determining if a usermetric vector is outside a user metric space, if only one metric valueis outside its corresponding metric range, then the user metric vectoris determined to be outside the metric space. In other embodiments,using less strict criteria for determining if a user metric vector isoutside a user metric space, a user metric vector is determined to beoutside the user metric space if all of the metric values of the usermetric vector are outside their corresponding metric ranges by a certaindegree. In various embodiments, the number of metric values that must beoutside their corresponding metric ranges, or the degree to which ametric value must be outside its corresponding metric range to make adetermination that the user metric vector is outside the metric spacewill vary, all such methods of determining whether a user metric vectoris outside a metric space are well within the scope of the presentinvention.

The second illustrated method of determining (608) that the user metricvector (606) is outside the user metric space (610) illustrated in FIG.13 includes calculating (810) a metric vector value (812) andcalculating (814) a metric space value (816) and comparing (818) themetric vector value (812) to the metric space value (816). One way ofcalculating a metric vector value is by using a predetermined formula toidentify a single value that is a function of the metric values of theuser metric and relational metrics of the user metric vector. In oneexemplary embodiment of the present invention, calculating a metricvector value includes averaging the metric values of the user metricvector. In another example embodiment, calculating a metric vector valueincludes prioritizing certain kinds of metrics or relational metrics andusing a weighted average based on the priority of the metric tocalculate a metric vector value.

In some exemplary embodiments, calculating (814) a metric space value(818) includes using a predetermined formula to determine a metric spacevalue that is a function of the minimum and maximum values of eachmetric range of the user metric space. In one example embodiment,calculating a metric space value includes finding the center point ofthe minimum and maximum value of the each metric range and thenaveraging the center points.

The illustrated method includes comparing (818) the metric space value(816) and the metric vector value (812). In various embodiments of thepresent invention, how the metric vector value and the metric spacevalue are compared to determine whether the metric vector is outside themetric space will vary. In one example embodiment, the metric vectorvalue is subtracted from the metric space value. If the result of thesubtraction is within a predetermined range, then the user metric vectoris determined to be within the metric space. In the same example, if theresult of the subtraction is not within the predetermined range, thenthe metric vector value is not determined to be within the metric space.

The illustrated methods of FIG. 13 are provided for explanation and notfor limitation. There are many other ways metric ranges and metricvalues can be compared, combined, manipulated, or otherwise used to makea determination that a user metric vector is outside a metric space. Allsuch ways of comparing, combining, manipulating, or otherwise usingmetric values and metric ranges to make a determination that a usermetric vector is outside a metric space are included within the scope ofthe present invention.

FIG. 14 is a data flow diagram illustrating an exemplary method ofidentifying (630) an action (315). In the method of FIG. 14, identifyingan action includes creating (624), in dependence upon the user metricvector (606), a dynamic action list (626). Typical dynamic action listsinclude action IDs identified dynamically in dependence upon the actionIDs included within metric action lists associated with the particularmetrics of a user's metric vector that are outside their correspondingmetric ranges of the user's metric space and the specific relationalmetrics that are outside their corresponding metric range or metricranges. Creating such a dynamic action list advantageously provides aset of action IDs tailored to administer devices in response to theuser's current condition.

In the method of FIG. 14, creating (624), in dependence upon the usermetric vector (606), a dynamic action list (626) includes identifying(752) a metric action list (622) for each user metric (206) and eachrelational metric of the user metric vector (606) having a value that isoutside a metric range of the user metric space. In many examples of themethod of FIG. 14, identifying (752) a metric action list (622) for eachuser metric (206) and relational metric (664) that is outside itscorresponding a metric range and for each relational metric that isoutside its corresponding metric range includes retrieving a referenceto the metric action list from a metric object previously identified asbeing outside its corresponding metric range when the user metric vectorwas determined to be outside the user metric space and retrieving areference to a metric action list from a relational metric previouslyidentified as being outside its corresponding metric range. The metricobjects outside their metric ranges are, in many examples, identifiedwhen the metric objects are compared with their metric ranges todetermine if the user metric vector is outside the metric space.

In many examples of the method of FIG. 14, a metric has a plurality ofassociated metric action lists. Each associated metric action listincludes a set of action IDs for execution in dependence upon the degreeand direction that the value of the metric is outside the metric range.In some examples of the method of FIG. 14 therefore, identifying (752) ametric action list (622) for each user metric (206) of the user metricvector (606) having a value that is outside a metric range of the usermetric space includes identifying a metric list in dependence upon adegree to which the value of each user metric of the user metric vectoris outside a metric range of the user metric space. In another exampleof the method of FIG. 14, identifying (752) a metric action list (622)for each user metric (206) of the user metric vector (606) having avalue that is outside a metric range of the user metric space includesidentifying a metric list in dependence upon a direction that the valueof each user metric of the user metric vector is outside a metric rangeof the user metric space.

In the method of FIG. 14, creating (624), in dependence upon the usermetric vector (606), a dynamic action list (626) includes retrieving(754) at least one action ID (315) from each metric action list (622).Some metric action lists include a plurality of action IDs and thereforemany examples of the method of FIG. 14 include retrieving a plurality ofaction IDs from the metric action lists associated with each metrichaving a value outside its corresponding metric range.

In the method of FIG. 14, creating (624), in dependence upon the usermetric vector (606), a dynamic action list (626) includes identifying(756) at least one action ID (315) for inclusion in the dynamic actionlist (626) in dependence upon the action IDs (315) retrieved from themetric action lists (622). In many examples of the method of FIG. 14,identifying (756) at least one action ID (315) for inclusion in thedynamic action list (626) in dependence upon the action IDs (315)retrieved from the metric action lists (622) includes identifying anaction ID retrieved directly from the metric action lists themselves forinclusion in the dynamic action list. That is, in some examples of themethod of FIG. 14 the same action ID retrieved from a metric action listis included in the dynamic action list.

In the method of FIG. 14, identifying (756) at least one action ID (315)for inclusion in the dynamic action list (626) in dependence upon theaction IDs (315) retrieved from the metric action lists (622) includescomparing (758) the action IDs (315) of the metric action lists (622)and omitting repetitious actions. In some examples of the method of FIG.14, omitting repetitious actions includes determining that the sameaction ID is included in more than one metric action list. In suchexamples, creating a dynamic action list includes identifying metricaction lists having the same action IDs and including the action ID onlyonce in the dynamic action list.

In the method of FIG. 14, identifying (756) at least one action ID (315)for inclusion in the dynamic action list (626) in dependence upon theaction IDs (315) retrieved from the metric action lists (622) includesretrieving (760) an action ID (315) from a dynamic action table (762) independence upon at least one action ID of the metric action lists. Inmany examples of the method of FIG. 14, a dynamic action table (762) isa data structure including action IDs indexed by other action IDs. Thatis, the dynamic action table is a data structure designed to indexpredetermined action IDs for inclusion in the dynamic action list independence upon the action IDs retrieved from the metric action lists.

Such a dynamic action table therefore is in many examples of the methodof FIG. 14 designed to identify conflicting actions retrieved from themetric action lists, identify superseding actions retrieved from themetric action list, as well as identify further actions not included inthe metric action lists. In some examples of the method of FIG. 14,identifying (756) at least one action ID (315) for inclusion in thedynamic action list (626) in dependence upon the action IDs (315)retrieved from the metric action lists (622) includes omittingconflicting actions. In many examples of the method of FIG. 14 a dynamicaction table is used to identify action IDs that have been predeterminedto conflict. For example, an action ID included in one metric actionlist that identifies a device controlling action to turn on a ceilingfan conflicts with an action ID identifying a device controlling actionto turn off the same ceiling fan. Such conflicting action IDs areomitted from the dynamic action list.

In some examples of the method of FIG. 14, identifying (756) at leastone action ID (315) for inclusion in the dynamic action list (626) independence upon the action IDs (315) retrieved from the metric actionlists (622) includes omitting superseded actions. A superseded action isan action that when executed administers the same device in the samedirection as another superseding action, but administers the device to alesser degree than the other superseding action. That is, an action issuperseded when another action administers the same device to a greaterdegree such that the execution of superseded action is cloaked byexecution of the superseding action. For example, the execution of anaction ID that results in changing the value of a current attribute of aceiling fan from “5” to “4” is superseded by the execution of an actionID that results in changing the same ceiling fan attribute from “5” to“2.” In many examples of the method of FIG. 14, a dynamic action tableis used to identify action IDs that have been predetermined to supersedeother actions IDs. Many examples of the method of FIG. 14 includeomitting the superseded action IDs from the dynamic action list andincluding the superseding action ID.

In the method of FIG. 14, identifying (756) at least one action ID (315)for inclusion in the dynamic action list (626) in dependence upon theaction IDs (315) retrieved from the metric action lists (622) includesidentifying an action ID for inclusion in the dynamic action list thatis not included in any of the identified metric action lists (622). Inmany examples of the method of FIG. 14, an action ID identified by alookup in the dynamic action table (762) is not included in any of theidentified metric action. In some of these examples, the dynamic actiontable is populated with action IDs that have been predetermined toaffect the same user condition when executed as other action IDs. Such adynamic action table is indexed to identify an action ID for executionwhen one or more other action IDs are retrieved from the metric actionlists. In this way, dynamic action tables advantageously provide avehicle for identifying and executing more actions to affect the user'scurrent condition.

For further explanation of identifying action IDs that are not includedin any metric action list associated with a user metric outside itscorresponding range, the following example is provided. Two user metricsof a user metric vector are above their corresponding metric ranges ofthe user's metric space. The first metric represents body temperatureand has a first action ID in its associated metric action list that whenexecuted results in turning on a ceiling fan. The second metricrepresents heart rate and has a second action ID in its associatedmetric list that when executed turns on an air conditioner. A lookup ina dynamic action table in dependence upon the first action ID and thesecond action ID retrieves a third action ID that is not included ineither metric action list of either metric. Executing the third actionID results in turning on the ceiling fan, turning on the airconditioner, and drawing automated window curtains. The added action ofdrawing automated window curtains is predetermined to affect the sameuser condition as turning on the air conditioner and the ceiling fan. Alookup on the dynamic action table identifies the third action ID forinclusion in the dynamic action list in dependence upon the first andsecond action IDs.

FIG. 15 is a data flow diagram illustrating an exemplary method ofidentifying (630) an action. In the method of FIG. 15, identifying anaction includes determining (970) the user's location (972). In manyexamples of the method of FIG. 15, determining the user's locationincludes retrieving, from the user metric vector, a reference to a usermetric (206) for location and retrieving the value of the user metricfor location. In other examples, of the method of FIG. 15, determiningthe user's location includes inferring the user's location such as byinferring the user's location from other metrics, or by identifyingchanges in device attributes caused by a user's direct administration ofa device, or any other method of inferring the user's location that willoccur to those of skill in the art.

In the method of FIG. 15, identifying an action includes determining(971) user movement (974). In some examples of the method of FIG. 15,determining user movement includes retrieving, from a user metricvector, a relational metric (664) representing a user's movement andretrieving the value of the relational metric. In some examples of themethod of FIG. 15, determining user movement includes retrieving, from auser metric vector, a plurality of relational metric (664) representingvarious aspects of a user's movement and retrieving the values of theplurality of relational metrics.

In the method of FIG. 15, identifying an action (630) includes selecting(975) an action ID (315) in dependence upon the user's location (972)and the user's movement (974). In the method of FIG. 15, selecting (975)an action ID in dependence upon the user's location and the user'smovement includes retrieving, from an action table, an action ID independence upon the user's location and user's movement.

In many examples of the method of FIG. 15, an action table (975)includes action IDs indexed by location and specific user movement. Intypical examples of the method of FIG. 15, the action IDs of the actiontable identify actions designed to administer specific devices whoseeffective range covers the user's current location and are designedadminister the device in a manner consistent with the user's currentmovement. For example, the user may be in a living room having a radiowhose effective range covers the living room. Furthermore, the actionmay be designed to slowly lower the volume of the radio as the userapproaches the location of the radio. A particular action ID selectedfrom the action table in dependence upon the user's location and user'smovement can advantageously provide location based device control.

Consider the following example. The user's metric vector indicates thatthe user's heart rate exceeds its corresponding metric range. The DMLidentifies and executes an action ID identifying an action to turn onthe user's music player and set the player to play music designated assoothing to the user. The DML also determines that the user is in hisliving room and the DML determines that the user is moving toward themusic player. Another action ID designed to lower the volume at a rateappropriate for the speed and direction of the user is identified andexecuted. The result of lowering the volume is that the volume appearsunchanged to the user.

Some examples of the method of FIG. 15 include identifying an action(630) by selecting (975) an action ID (315) in dependence upon theuser's location (972) and the user's movement (974) and by identifyingan action by creating a dynamic action list. That is, more than onemethod of identifying an action are implemented in conjunction and inmany cases, many actions are identified and executed. In other examples,identifying an action is carried out by selecting (975) an action ID(315) in dependence upon the user's location (972) and the user'smovement (974), or by identifying an action by creating a dynamic actionlist, or by using any other method of identifying an action that willoccur to those of skill in the art.

It will be understood from the foregoing description that modificationsand changes may be made in various embodiments of the present inventionwithout departing from its true spirit. The descriptions in thisspecification are for purposes of illustration only and are not to beconstrued in a limiting sense. The scope of the present invention islimited only by the language of the following claims.

1. A method for administering devices, the method comprising: receivinga plurality of user metrics; creating a relational metric in dependenceupon the plurality of user metrics; creating a user metric vectorcomprising at least one user metric and at least one relational metric;creating a user metric space comprising a plurality of metric ranges;determining whether the user metric vector is outside the user metricspace; if the user metric vector is outside a user metric space,identifying an action; and executing the action.
 2. The method of claim1 wherein creating a relational metric in dependence upon the pluralityof user metrics comprises filtering the user metrics.
 3. The method ofclaim 2 wherein creating a relational metric in dependence upon theplurality of user metrics comprises determining a relationship between afirst filtered user metric and a second filtered user metric.
 4. Themethod of claim 3 wherein determining a relationship between a firstfiltered user metric and a second filtered user metric comprisescomparing a first filtered user metric with a second filtered usermetric.
 5. The method of claim 3 wherein creating a relational metric independence upon the plurality of user metrics comprises determining amagnitude of the relationship between the first filtered user metric andthe second filtered user metric.
 6. The method of claim 1 whereincreating relational metric in dependence upon the plurality of usermetrics comprises determining whether the plurality of user metricsmatch a predefined metric pattern.
 7. The method of claim 6 comprisingretrieving a relational metric, if the plurality of user metrics matchthe predefined metric pattern.
 8. The method of claim 1 wherein creatinga user metric vector comprising at least one user metric and at leastone relational metric comprises associating at least one user metricwith the user metric vector and associating at least one relationalmetric with the user metric vector.
 9. The method of claim 1, whereinidentifying an action comprises: determining a user's location; andselecting an action ID in dependence upon the user's location.
 10. Themethod of claim 9, wherein identifying an action comprises: determininguser movement; and selecting an action ID in dependence upon the usermovement.
 11. A system for administering devices, the system comprising:means for receiving a plurality of user metrics; means for creating arelational metric in dependence upon the plurality of user metrics;means for creating a user metric vector comprising at least one usermetric and at least one relational metric; means for creating a usermetric space comprising a plurality of metric ranges; means fordetermining whether the user metric vector is outside the user metricspace; if the user metric vector is outside a user metric space, meansfor identifying an action; and means for executing the action.
 12. Thesystem of claim 11 wherein means for creating a relational metric independence upon the plurality of user metrics comprises means forfiltering the user metrics.
 13. The system of claim 12 wherein means forcreating a relational metric in dependence upon the plurality of usermetrics comprises means for determining a relationship between a firstfiltered user metric and a second filtered user metric.
 14. The systemof claim 13 wherein means for determining a relationship between a firstfiltered user metric and a second filtered user metric comprises meansfor comparing a first filtered user metric with a second filtered usermetric.
 15. The system of claim 13 wherein means for creating arelational metric in dependence upon the plurality of user metricscomprises means for determining a magnitude of the relationship betweenthe first filtered user metric and the second filtered user metric. 16.The system of claim 11 wherein means for creating relational metric independence upon the plurality of user metrics comprises means fordetermining whether the plurality of user metrics match a predefinedmetric pattern.
 17. The system of claim 16 comprising means forretrieving a relational metric, if the plurality of user metrics matchthe predefined metric pattern.
 18. The system of claim 11 wherein meansfor creating a user metric vector comprising at least one user metricand at least one relational metric comprises means for associating atleast one user metric with the user metric vector and means forassociating at least one relational metric with the user metric vector.19. The system of claim 11, wherein means for identifying an actioncomprises: means for determining a user's location; and means forselecting an action ID in dependence upon the user's location.
 20. Themethod of claim 19, wherein means for identifying an action comprises:means for determining user movement; and means for selecting an actionID in dependence upon the user movement.
 21. A computer program productfor administering devices, the computer program product comprising: arecording medium; means, recorded on the recording medium, for receivinga plurality of user metrics; means, recorded on the recording medium,for creating a relational metric in dependence upon the plurality ofuser metrics; means, recorded on the recording medium, for creating auser metric vector comprising at least one user metric and at least onerelational metric; means, recorded on the recording medium, for creatinga user metric space comprising a plurality of metric ranges; means,recorded on the recording medium, for determining whether the usermetric vector is outside the user metric space; if the user metricvector is outside a user metric space, means, recorded on the recordingmedium, for identifying an action; and means, recorded on the recordingmedium, for executing the action.
 22. The computer program product ofclaim 21 wherein means, recorded on the recording medium, for creating arelational metric in dependence upon the plurality of user metricscomprises means, recorded on the recording medium, for filtering theuser metrics.
 23. The computer program product of claim 22 whereinmeans, recorded on the recording medium, for creating a relationalmetric in dependence upon the plurality of user metrics comprises means,recorded on the recording medium, for determining a relationship betweena first filtered user metric and a second filtered user metric.
 24. Thecomputer program product of claim 23 wherein means, recorded on therecording medium, for determining a relationship between a firstfiltered user metric and a second filtered user metric comprises means,recorded on the recording medium, for comparing a first filtered usermetric with a second filtered user metric.
 25. The computer programproduct of claim 23 wherein means, recorded on the recording medium, forcreating a relational metric in dependence upon the plurality of usermetrics comprises means, recorded on the recording medium, fordetermining a magnitude of the relationship between the first filtereduser metric and the second filtered user metric.
 26. The computerprogram product of claim 25 wherein means, recorded on the recordingmedium, for creating relational metric in dependence upon the pluralityof user metrics comprises means, recorded on the recording medium, fordetermining whether the plurality of user metrics match a predefinedmetric pattern.
 27. The computer program product of claim 26 comprisingmeans, recorded on the recording medium, for retrieving a relationalmetric, if the plurality of user metrics match the predefined metricpattern.
 28. The computer program product of claim 21 wherein means,recorded on the recording medium, for creating a user metric vectorcomprising at least one user metric and at least one relational metriccomprises means, recorded on the recording medium, for associating atleast one user metric with the user metric vector and means, recorded onthe recording medium, for associating at least one relational metricwith the user metric vector.
 29. The computer program product of claim21, wherein means, recorded on the recording medium, for identifying anaction comprises: means, recorded on the recording medium, fordetermining a user's location; and means, recorded on the recordingmedium, for selecting an action ID in dependence upon the user'slocation.
 30. The computer program product of claim 29, wherein means,recorded on the recording medium, for identifying an action comprises:means, recorded on the recording medium, for determining user movement;and means, recorded on the recording medium, for selecting an action IDin dependence upon the user movement.